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<bibfile>

<paper id="1">
<key>185-</key>
<inproceedings>
<author>
<person>Majid Ghaderi</person>
<person>Ashwin Sridharan</person>
<person>Hui Zang</person>
<person>Don Towsley</person>
<person>Rene Cruz</person>
</author>
<title>Modeling TCP in a Multi-Rate Multi-User CDMA System</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of IFIP-Networking 2007</booktitle>
<journal>IFIP-Networking 2007</journal>
<address>Atlanta, Georgia</address>
<pdf>uploads/1569018175.pdf</pdf>
<month>--05--</month>
<year>2007</year>
</inproceedings>
<pubdate>20070501</pubdate>
</paper>

<paper id="2">
<key>adya-architecture</key>
<inproceedings>
<author>
<person>Atul Adya</person>
<person>Paramvir Bahl</person>
<person>Ranveer Chandra</person>
<person>Lili Qiu</person>
</author>
<title>Architecture and techniques for diagnosing faults in IEEE 802.11 infrastructure networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Tenth Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<pages>30-44</pages>
<month>--09--</month>
<year>2004</year>
<address>Philadelphia, PA</address>
<url>http://doi.acm.org/10.1145/1023720.1023724</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20040901</pubdate>
</paper>

<paper id="3">
<key>anderson-challenges</key>
<inproceedings>
<author>
<person>Eric Anderson</person>
<person>Caleb Phillips</person>
<person>Gary Yee</person>
<person>Douglas Sicker</person>
<person>Dirk Grunwald</person>
</author>
<title>Challenges in Deploying Steerable Wireless Testbeds</title>
<booktitle>TridentCom 2010</booktitle>
<pages>231-240</pages>
<year>2010</year>
<month>--05--</month>
<editor>Magedanz, Thomas and Gavras, Anastasius and Nguyen, Huu-Thanh and Chase, Jeffrey S.</editor>
<volume>46</volume>
<series>Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering</series>
<address>Germany</address>
<url>http://www.cs.colorado.edu/department/publications/reports/docs/CU-CS-1058-09.pdf</url>
<publisher>Springer-Verlag</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>cu_cu_wart</keywords>
<category>wireless-meas, crawdad</category>
<refnames><refname>cu/cu_wart</refname>
</refnames>
</inproceedings>
<pubdate>20100501</pubdate>
</paper>

<paper id="4">
<key>anderson-contagion</key>
<inproceedings>
<author>
<person>Everett Anderson</person>
<person>Kevin Eustice</person>
<person>Shane Markstrum</person>
<person>Mark Hansen</person>
<person>Peter Reiher</person>
</author>
<title>Mobile Contagion: Simulation of Infection and Defense</title>
<booktitle>Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation (PADS'05)</booktitle>
<month>--06--</month>
<year>2005</year>
<pages>80-87</pages>
<url>http://portal.acm.org/citation.cfm?id=1069810.1070163</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="5">
<key>anderson-directionality-sigmetrics</key>
<inproceedings>
<author>
<person>Eric Anderson</person>
<person>Caleb Phillips</person>
<person>Kevin Bauer</person>
<person>Douglas Sicker</person>
<person>Dirk Grunwald</person>
</author>
<title>Modeling Directionality in Wireless Networks [Extended Abstract]</title>
<booktitle>ACM SigMetrics</booktitle>
<year>2008</year>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cu_antenna</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cu/antenna</refname>
</refnames>
</inproceedings>
<pubdate>20080001</pubdate>
</paper>

<paper id="6">
<key>anderson-directionality-tr</key>
<techreport>
<author>
<person>Eric Anderson</person>
<person>Caleb Phillips</person>
<person>Douglas Sicker</person>
<person>Dirk Grunwald</person>
</author>
<title>Modeling Environmental Effects on Directionality in Wireless Networks</title>
<institution>University of Colorado at Boulder</institution>
<year>2008</year>
<url>http://www.cs.colorado.edu/department/publications/reports/docs/CU-CS-1044-08.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cu_antenna</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cu/antenna</refname>
</refnames>
</techreport>
<pubdate>20080001</pubdate>
</paper>

<paper id="7">
<key>anderson-directionality-winmee</key>
<inproceedings>
<author>
<person>Eric Anderson</person>
<person>Caleb Phillips</person>
<person>Douglas Sicker</person>
<person>Dirk Grunwald</person>
</author>
<title>Modeling Environmental Effects on Directionality in Wireless Networks</title>
<booktitle>5th International workshop on Wireless Network Measurements (WiNMee)</booktitle>
<year>2009</year>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cu_antenna</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cu/antenna</refname>
</refnames>
</inproceedings>
<pubdate>20090001</pubdate>
</paper>

<paper id="8">
<key>anderson-directionality-wiopt</key>
<inproceedings>
<author>
<person>Eric Anderson</person>
<person>Gary Yee</person>
<person>Caleb Phillips</person>
<person>Douglas Sicker</person>
<person>Dirk Grunwald</person>
</author>
<title>The Impact of Directional Antenna Models on Simulation Accuracy</title>
<booktitle>7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)</booktitle>
<year>2009</year>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cu_antenna</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cu/antenna</refname>
</refnames>
</inproceedings>
<pubdate>20090001</pubdate>
</paper>

<paper id="9">
<key>andrews-cdma</key>
<inproceedings>
<author>
<person>Matthew Andrews</person>
<person>Lisa Zhang</person>
</author>
<title>A CDMA Data Measurement and Analysis Tool</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/02-02.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="10">
<key>aschenbruck-traffic</key>
<inproceedings>
<author>
<person>Nils Aschenbruck</person>
<person>Matthias Frank</person>
<person>Peter Martini</person>
<person>Jens Toelle</person>
</author>
<title>Traffic Measurement and Statistical Analysis in a Disaster Area Scenario</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Aschenbruck.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="11">
<key>ault-neighbor</key>
<inproceedings>
<author>
<person>Aaron Ault</person>
<person>Edward Coyle</person>
<person>Xuan Zhong</person>
</author>
<title>K-Nearest-Neighbor Analysis of Received Signal Strength Distance Estimation Across Environments</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Ault.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="12">
<key>bahl-breathing</key>
<article>
<author>
<person>Paramvir (Victor) Bahl</person>
<person>Mohammad T. Hajiaghayi</person>
<person>Kamal Jain</person>
<person>Sayyed Vahab Mirrokni</person>
<person>Lili Qiu</person>
<person>Amin Saberi</person>
</author>
<title>Cell Breathing in Wireless LANs: Algorithms and Evaluation</title>
<journal>IEEE Transactions on Mobile Computing</journal>
<volume>6</volume>
<number>2</number>
<year>2007</year>
<issn>1536-1233</issn>
<pages>164-178</pages>
<doi>http://doi.ieeecomputersociety.org/10.1109/TMC.2007.20</doi>
<publisher>IEEE Computer Society</publisher>
<address>Los Alamitos, CA, USA</address>
<url>http://www.cs.utexas.edu/~lili/papers/pub/TMC2006.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>ucsd_sigcomm2001</keywords>
<keywords>stanford_gates</keywords>
<keywords>ibm_watson</keywords>
<keywords>crawdad</keywords>
<refnames><refname>ucsd/sigcomm2001</refname>
</refnames>
</article>
<pubdate>20070001</pubdate>
</paper>

<paper id="13">
<key>bakken04-data</key>
<article>
<author>
<person>David E. Bakken</person>
<person>Rupa Parameswaran</person>
<person>Douglas M. blough</person>
<person>Andy A. Franz</person>
<person>Ty J. Palmer</person>
</author>
<title>Data obfuscation: anonymity and desensitization of usable data sets</title>
<journal>IEEE Security &amp; Privacy</journal>
<pages>34-41</pages>
<month>--11--</month>
<year>2004</year>
<url>http://dx.doi.org/10.1109/MSP.2004.97</url>
<abstract>In some domains, the need for data privacy and data sharing conflict. Data 
obfuscation addresses this dilemma by extending several existing technologies 
and defining obfuscation properties that quantify the technologies' usefulness 
and privacy preservation. </abstract>
<category>meta-meas</category>
</article>
<pubdate>20041101</pubdate>
</paper>

<paper id="14">
<key>balachandran-behavior</key>
<inproceedings>
<author>
<person>Anand Balachandran</person>
<person>Geoffrey M. Voelker</person>
<person>Paramvir Bahl</person>
<person>P. Venkat Rangan</person>
</author>
<title>Characterizing User Behavior and Network Performance in a Public Wireless LAN</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ucsd_sigcomm2001</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the 2002 ACM SIGMETRICS Conference</booktitle>
<pages>195-205</pages>
<month>--06--</month>
<year>2002</year>
<address>Marina Del Rey, CA</address>
<publisher>ACM Press</publisher>
<copyright>ACM</copyright>
<url>http://doi.acm.org/10.1145/511334.511359</url>
<keyword>wireless network, workload characterization</keyword>
<abstract>This paper presents and analyzes user behavior and network performance in a 
public-area wireless network using a workload captured at a well-attended ACM 
conference. The goals of our study are: (1) to extend our understanding of 
wireless user behavior and wireless network performance; (2) to characterize 
wireless users in terms of a parameterized model for use with analytic and 
simulation studies involving wireless LAN traffic; and (3) to apply our 
workload analysis results to issues in wireless network deployment, such as 
capacity planning, and potential network optimizations, such as algorithms for 
load balancing across multiple access points (APs) in a wireless network. </abstract>
<category>wireless-meas,crawdad</category>
<refnames><refname>ucsd/sigcomm2001</refname>
</refnames>
</inproceedings>
<pubdate>20020601</pubdate>
</paper>

<paper id="15">
<key>balasubramanian-dtn</key>
<inproceedings>
<author>
<person>Aruna Balasubramanian</person>
<person>Brian Neil Levine</person>
<person>Arun Venkataramani</person>
</author>
<title>DTN Routing as a Resource Allocation Problem</title>
<booktitle>Proc. ACM Sigcomm</booktitle>
<month>--08--</month>
<year>2007</year>
<address>Kyoto, Japan</address>
<url>http://www.sigcomm.org/ccr/drupal/?q=node/273</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_diesel</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20070801</pubdate>
</paper>

<paper id="16">
<key>balasubramanian-hybrid</key>
<inproceedings>
<author>
<person>Aruna Balasubramanian</person>
<person>Brian Neil Levine</person>
<person>Arun Venkataramani</person>
</author>
<title>Enhancing interactive web applications in hybrid networks</title>
<keywords>crawdad</keywords>
<keywords>umass/diesel</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>MobiCom '08: Proceedings of the 14th ACM international conference on Mobile computing and networking</booktitle>
<year>2008</year>
<isbn>978-1-60558-096-8</isbn>
<pages>70-80</pages>
<address>San Francisco, California, USA</address>
<doi>http://doi.acm.org/10.1145/1409944.1409954</doi>
<url>http://doi.acm.org/10.1145/1409944.1409954</url>
<publisher>ACM</publisher>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20080001</pubdate>
</paper>

<paper id="17">
<key>balasubramanian-interactive</key>
<article>
<author>
<person>Aruna Balasubramanian</person>
<person>Ratul Mahajan</person>
<person>Arun Venkataramani</person>
<person>Brian Neil Levine</person>
<person>John Zahorjan</person>
</author>
<title>Interactive wifi connectivity for moving vehicles</title>
<keywords>crawdad</keywords>
<keywords>umass/diesel</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>SIGCOMM Comput. Commun. Rev.</journal>
<volume>38</volume>
<number>4</number>
<year>2008</year>
<issn>0146-4833</issn>
<pages>427-438</pages>
<doi>http://doi.acm.org/10.1145/1402946.1403006</doi>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<refnames><refname>umass/diesel</refname>
</refnames>
</article>
<pubdate>20080001</pubdate>
</paper>

<paper id="18">
<key>balasubramanian-search</key>
<inproceedings>
<author>
<person>Aruna Balasubramanian</person>
<person>Yun Zhou</person>
<person>W. Bruce Croft</person>
<person>Brian. N. Levine</person>
<person>Arun Venkataramani</person>
</author>
<title>Web Search From a Bus</title>
<booktitle>ACM Mobicom Workshop on Challenged Networks (CHANTS 07)</booktitle>
<address>Montreal, Canada</address>
<month>--09--</month>
<year>2007</year>
<url>http://portal.acm.org/citation.cfm?id=1287803</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_diesel</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20070901</pubdate>
</paper>

<paper id="19">
<key>balazinska-wireless</key>
<inproceedings>
<author>
<person>Magdalena Balazinska</person>
<person>Paul Castro</person>
</author>
<title>Characterizing Mobility and Network Usage in a Corporate Wireless Local-Area Network</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ibm_watson</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<pages>303-316</pages>
<month>--05--</month>
<year>2003</year>
<address>San Francisco, CA</address>
<publisher>USENIX Association</publisher>
<url>http://www.usenix.org/events/mobisys03/tech/balazinska.html</url>
<keyword>mobile computing, wireless network, 802.11, Wi-Fi, WLAN, workload characterization</keyword>
<abstract>Wireless local-area networks are becoming increasingly popular. They are 
commonplace on university campuses and inside corporations, and they have 
started to appear in public areas. It is thus becoming increasingly important 
to understand user mobility patterns and network usage characteristics on 
wireless networks. Such an understanding would guide the design of applications 
geared toward mobile environments (e.g., pervasive computing applications), 
would help improve simulation tools by providing a more representative workload 
and better user mobility models, and could result in a more effective 
deployment of wireless network components. \par Several studies have recently 
been performed on wireless university campus networks and public networks. In 
this paper, we complement previous research by presenting results from a four 
week trace collected in a large corporate environment. We study user mobility 
patterns and introduce new metrics to model user mobility. We also analyze user 
and load distribution across access points. We compare our results with those 
from previous studies to extract and explain several network usage and mobility 
characteristics. &lt;p&gt; We find that average user transfer-rates follow a 
power law. Load is unevenly distributed across access points and is influenced 
more by which users are present than by the number of users. We model user 
mobility with persistence and prevalence . Persistence reflects session 
durations whereas prevalence reflects the frequency with which users visit 
various locations. We find that the probability distributions of both measures 
follow power laws. </abstract>
<category>wireless-meas,crawdad</category>
<refnames><refname>ibm/watson</refname>
</refnames>
</inproceedings>
<pubdate>20030501</pubdate>
</paper>

<paper id="20">
<key>banerjee-relays</key>
<inproceedings>
<author>
<person>Nilanjan Banerjee</person>
<person>Mark D. Corner</person>
<person>Don Towsley</person>
<person>Brian N. Levine</person>
</author>
<title>Relays, base stations, and meshes: enhancing mobile networks with infrastructure</title>
<keywords>crawdad</keywords>
<keywords>umass/diesel</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>MobiCom '08: Proceedings of the 14th ACM international conference on Mobile computing and networking</booktitle>
<year>2008</year>
<isbn>978-1-60558-096-8</isbn>
<pages>81-91</pages>
<address>San Francisco, California, USA</address>
<doi>http://doi.acm.org/10.1145/1409944.1409955</doi>
<url>http://doi.acm.org/10.1145/1409944.1409955</url>
<publisher>ACM</publisher>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20080001</pubdate>
</paper>

<paper id="21">
<key>banerjee-throwboxes</key>
<inproceedings>
<author>
<person>Nilanjan Banerjee</person>
<person>Mark D. Corner</person>
<person>Brian Levine</person>
</author>
<title>An Energy-Efficient Architecture for DTN Throwboxes</title>
<booktitle>Proceedings of Infocom 2007)</booktitle>
<address>Anchorage, Alaska</address>
<month>--05--</month>
<year>2007</year>
<url>http://www.cs.umass.edu/~nilanb/papers/banerjee06-39.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_diesel</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20070501</pubdate>
</paper>

<paper id="22">
<key>barsocchi-rural_wifi</key>
<inproceedings>
<author>
<person>Paolo Barsocchi</person>
<person>Gabriele Oligeri</person>
<person>Francesco Potort&#236;</person>
</author>
<title>Frame error model in rural Wi-Fi networks</title>
<booktitle>proceedings of the International Symposium on Modeling and Optimization (Wiopt)</booktitle>
<pages>41-46</pages>
<year>2007</year>
<address>Limassol (CY)</address>
<month>--04--</month>
<publisher>ACM</publisher>
<abstract>Commonly used frame loss models for simulations over Wi-Fi channels assume a 
simple double regression model with threshold. This model is widely accepted, 
but few measurements are available in the literature that try to validate it. 
As far as we know, none of them is based on field trials at the frame level. We 
present a series of measurements for relating transmission distance and packet 
loss on a Wi-Fi network in rural areas and propose a model that relates 
distance with packet loss probability. We show that a simple double regression 
propagation model like the one used in the ns-2 simulator can miss important 
transmission impairments that are apparent even at short transmitter-receiver 
distances. Measurements also show that packet loss at the frame level is a 
Bernoullian process for time spans of few seconds. We relate the packet loss 
probability to the received signal level using standard models for additive 
white Gaussian noise channels. The resulting model is much more similar to the 
measured channels than the simple models where all packets are received when 
the distance is below a given threshold and all are lost when the threshold is 
exceeded. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>isti_rural</keywords>
<keywords>crawdad</keywords>
<url>http://fly.isti.cnr.it/curriculum/papers/pdf/Rural-model-Winmee07.pdf</url>
<category>crawdad</category>
<refnames><refname>isti/rural</refname>
</refnames>
</inproceedings>
<pubdate>20070401</pubdate>
</paper>

<paper id="23">
<key>bauer-unlinkability</key>
<inproceedings>
<author>
<person>Kevin Bauer</person>
<person>Damon McCoy</person>
<person>Ben Greenstein</person>
<person>Dirk Grunwald</person>
<person>Douglas Sicker</person>
</author>
<title>Physical Layer Attacks on Unlinkability in Wireless LANs</title>
<booktitle>Proceedings of the Ninth Privacy Enhancing Technologies Symposium (PETS 2009)</booktitle>
<year>2009</year>
<month>--08--</month>
<address>Seattle, WA, USA</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cu_rssi</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cu/rssi</refname>
</refnames>
</inproceedings>
<pubdate>20090801</pubdate>
</paper>

<paper id="24">
<key>benabdesslem-mobile</key>
<inproceedings>
<author>
<person>Ben Abdesslem, Fehmi</person>
<person>Parris, Iain</person>
<person>Henderson, Tristan</person>
</author>
<title>Mobile Experience Sampling: Reaching the Parts of Facebook Other Methods Cannot Reach</title>
<booktitle>Proceedings of the Privacy and Usability Methods Pow-Wow (PUMP)</booktitle>
<address>Dundee, UK</address>
<year>2010</year>
<month>--09--</month>
<publisher>British Computer Society</publisher>
<url>http://scone.cs.st-andrews.ac.uk/pump2010/papers/benabdesslem.pdf</url>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>st_andrews_locshare</keywords>
<category>wireless-meas, crawdad</category>
<refnames><refname>st_andrews/locshare</refname>
</refnames>
</inproceedings>
<pubdate>20100901</pubdate>
</paper>

<paper id="25">
<key>biermann-betrayed</key>
<article>
<author><person>Kai Biermann</person>
</author>
<title>Betrayed by our own data</title>
<journal>Zeit Online</journal>
<year>2011</year>
<month>--03--</month>
<url>http://www.zeit.de/digital/datenschutz/2011-03/data-protection-malte-spitz</url>
<keywords>wireless</keywords>
<keywords>spitz_cellular</keywords>
<refnames><refname>spitz/cellular</refname>
</refnames>
</article>
<pubdate>20110301</pubdate>
</paper>

<paper id="26">
<key>bigwood-networking</key>
<inproceedings>
<author>
<person>Greg Bigwood</person>
<person>Devan Rehunathan</person>
<person>Martin Bateman</person>
<person>Tristan Henderson</person>
<person>Saleem Bhatti</person>
</author>
<title>Exploiting Self-Reported Social Networks for Routing in Ubiquitous Computing Environments</title>
<booktitle>IEEE International Conference on Wireless and Mobile Computing, Networking and Communication (WiMob '08)</booktitle>
<year>2008</year>
<month>October</month>
<publisher>IEEE</publisher>
<pages>484-489</pages>
<address>Avignon, France</address>
<url>http://www.cs.st-andrews.ac.uk/~dr/publications/sauce2008-brbhb2008.pdf</url>
<doi>10.1109/WiMob.2008.86</doi>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>st_andrews_sassy</keywords>
<category>wireless-meas, crawdad</category>
<refnames><refname>st_andrews/sassy</refname>
</refnames>
</inproceedings>
<pubdate>2008to01</pubdate>
</paper>

<paper id="27">
<key>bishop04-how</key>
<inproceedings>
<author>
<person>Matt Bishop</person>
<person>Bhume Bhumiratana</person>
<person>Rick Crawford</person>
<person>Karl Levitt</person>
</author>
<title>How to Sanitize Data</title>
<booktitle>Proceedings of the Ninth International Workshop on Enterprise Security</booktitle>
<month>--06--</month>
<year>2004</year>
<address>Modena, Italy</address>
<url>http://ieeexplore.ieee.org/iel5/9472/30049/01376836.pdf</url>
<abstract>Balancing the needs of a data analyst with the privacy needs of a data provider 
is a key issue when data is sanitized. This work treats both the requirements 
of the analyst and the privacy expectations as policies, and composes the two 
policies to detect conflicts. The result can be applied to an intermediate data 
representation to sanitize the relevant parts of the data. We conclude that 
this method has promise, but more work is needed to determine its effectiveness 
and limits. </abstract>
<category>meta-meas</category>
</inproceedings>
<pubdate>20040601</pubdate>
</paper>

<paper id="28">
<key>bishop-problems-sanitizing</key>
<inproceedings>
<author>
<person>Matt Bishop</person>
<person>Rick Crawford</person>
<person>Bhume Bhumiratana</person>
<person>Lisa Clark</person>
<person>Karl Levitt</person>
</author>
<title>Some Problems in Sanitizing Network Data</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 15th IEEE International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETIS '06)</booktitle>
<mon>-06-</mon>
<year>2006</year>
<pages>307-312</pages>
<address>Los Alamitos, CA, USA</address>
<keyword>sanitizing, network data</keyword>
<url>http://doi.ieeecomputersociety.org/10.1109/WETICE.2006.62</url>
<doi>http://doi.ieeecomputersociety.org/10.1109/WETICE.2006.62</doi>
<abstract>The problem of removing sensitive information from data before it is released 
publicly, or turned over to less trusted analysts, underlies much of the 
unwillingness to share data. The solution is to sanitize, or deidentify, parts 
of the data. When dealing with network addresses, the set of available 
addresses is finite. This limits some aspects of the sanitization. We analyze 
this problem in detail, and suggest approaches to ameliorate it. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="29">
<key>blinn-hotspot</key>
<inproceedings>
<author>
<person>David P. Blinn</person>
<person>Tristan Henderson</person>
<person>David Kotz</person>
</author>
<title>Analysis of a Wi-Fi Hotspot Network</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>1-6</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://portal.acm.org/citation.cfm?id=1072431</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="30">
<key>boc-mobility</key>
<inproceedings>
<author>
<person>Mathias Boc</person>
<person>Anne Fladenmuller</person>
<person>Marcelo Dias de Amorium</person>
</author>
<title>Towards self-characterization of user mobility patterns</title>
<booktitle>Proceedings of the 16th IST Mobile and Wireless Communications Summit</booktitle>
<month>--07--</month>
<year>2007</year>
<pages>1-5</pages>
<address>Budapest, Hungary</address>
<url>http://dx.doi.org/10.1109/ISTMWC.2007.4299098</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20070701</pubdate>
</paper>

<paper id="31">
<key>boc-otiy</key>
<inproceedings>
<author>
<person>Mathias Boc</person>
<person>Anne Fladenmuller</person>
<person>Marcelo Dias de Amorium</person>
</author>
<title>Otiy: Locators tracking nodes</title>
<booktitle>Proceedings of CoNext 2007</booktitle>
<address>New York, NY, USA</address>
<month>--12--</month>
<year>2007</year>
<url>http://arxiv.org/pdf/0709.2252</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20071201</pubdate>
</paper>

<paper id="32">
<key>burgess-attacks</key>
<inproceedings>
<author>
<person>John Burgess</person>
<person>George Dean Bissias</person>
<person>Mark D. Corner</person>
<person>Brian Neil Levine</person>
</author>
<title>Surviving attacks on disruption-tolerant networks without authentication</title>
<booktitle>MobiHoc '07: Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing</booktitle>
<year>2007</year>
<pages>61-70</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_diesel</keywords>
<keywords>cambrdge_haggle</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1288107.1288116</doi>
<url>http://doi.acm.org/10.1145/1288107.1288116</url>
<publisher>ACM Press</publisher>
<abstract>Disruption-Tolerant Networks (DTNs) deliver data in network environments 
composed of intermittently connected nodes. Just as in traditional networks, 
malicious nodes within a DTN may attempt to delay or destroy data in transit to 
its destination. Such attacks include dropping data, flooding the network with 
extra messages, corrupting routing tables, and counterfeiting network 
acknowledgments. Many existing methods for securing routing protocols require 
authentication supported by mechanisms such as a public key infrastructure, 
which is difficult to deploy and operate in a DTN, where connectivity is 
sporadic. Furthermore, the complexity of such mechanisms may dissuade node 
participation so strongly that potential attacker impacts are dwarfed by the 
loss of contributing participants. In this paper, we use connectivity traces 
from our UMass Diesel- Net project and the Haggle project to quantify routing 
attack effectiveness on a DTN that lacks security. We introduce plausible 
attackers and attack modalities and provide complexity results for the 
strongest of attackers. We show that the same routing with packet replication 
used to provide robustness in the face of unpredictable mobility allows the 
network to gracefully survive attacks. In the case of the most effective 
attack, acknowledgment counterfeiting, we show a straightforward defense that 
uses cryptographic hashes but not a central authority. We conclude that 
disruption-tolerant networks are extremely robust to attack; in our 
trace-driven evaluations, an attacker that has compromised 30% of all nodes 
reduces delivery rates from 70% to 55%, and to 20% with knowledge of future 
events. By comparison, contemporaneously connected networks are significantly 
more fragile </abstract>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="33">
<key>burgess-maxprop</key>
<inproceedings>
<author>
<person>John Burgess</person>
<person>Brian Gallagher</person>
<person>David Jensen</person>
<person>Brian Neil Levine</person>
</author>
<title>MaxProp: Routing for Vehicle-Based Disruption-Tolerant Networking</title>
<booktitle>Proceedings of IEEE Infocom 2006</booktitle>
<month>--04--</month>
<year>2006</year>
<address>Barcelona, Spain</address>
<url>http://prisms.cs.umass.edu/brian/pubs/burgess.infocom2006.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_diesel</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="34">
<key>calegari-ctg</key>
<inproceedings>
<author>
<person>Roberta Calegari</person>
<person>Mirco Musolesi</person>
<person>Franco Raimondi</person>
<person>Cecilia Mascolo</person>
</author>
<title>CTG: A Connectivity Trace Generator for Testing the Performance of Opportunistic Mobile Systems</title>
<booktitle>Proceedings of the European Software Engineering Conference and the International ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE07)</booktitle>
<month>--09--</month>
<year>2007</year>
<address>Dubrovnik, Croatia</address>
<url>http://www.cs.ucl.ac.uk/staff/m.musolesi/papers/esec07.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20070901</pubdate>
</paper>

<paper id="35">
<key>campos-user-mobility</key>
<inproceedings>
<author>
<person>Carlos Alberto V. Campos</person>
<person>Luis Felipe M. de Moraes</person>
</author>
<title>Investigating the User Mobility in Wireless Mobile Networks through Real Measurements</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceeding of the 2nd CoNEXT Conference</booktitle>
<year>2006</year>
<month>--12--</month>
<url>http://www.ravel.ufrj.br/arquivosPublicacoes/conext06-beto.pdf</url>
<address>Lisboa, Portugal</address>
<category>wireless-meas, crawdad</category>
</inproceedings>
<pubdate>20061201</pubdate>
</paper>

<paper id="36">
<key>carreras-malware</key>
<inproceedings>
<author>
<person>I.Carreras</person>
<person>D. Miorandi</person>
<person>Geoffrey S. Canright</person>
<person>Kenth Engo-Monsen</person>
</author>
<title>Understanding the Spread of Epidemics in Highly Partitioned Mobile Networks</title>
<booktitle>Proceedings of the 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2006)</booktitle>
<month>--12--</month>
<year>2006</year>
<address>Cavalese, Italy</address>
<url>http://www.create-net.it/~icarreras/docs/bionetics2006.pdf</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>umass_diesel</keywords>
<keywords>mit_reality</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20061201</pubdate>
</paper>

<paper id="37">
<key>chaintreau-diameter</key>
<inproceedings>
<author>
<person>A. Chaintreau</person>
<person>A. Mtibaa</person>
<person>L. Massouli&#233;</person>
<person>C. Diot</person>
</author>
<title>Diameter of Opportunistic Mobile Networks</title>
<booktitle>Proceedings of ACM Sigcomm CoNext</booktitle>
<year>2007</year>
<month>--12--</month>
<note>also available as Thomson technical report CR-PRL-2007-07-0001</note>
<otherinfo>also available as technical report CR-PRL-2007-07-0001</otherinfo>
<url>http://www.thlab.net/~chaintre/pub/chaintreau07diameter.pdf</url>
<category>wireless-meas,crawdad</category>
<refnames><refname>cambridge/haggle</refname>
</refnames>
</inproceedings>
<pubdate>20071201</pubdate>
</paper>

<paper id="38">
<key>chaintreau-opportunistic</key>
<inproceedings>
<author>
<person>Augustin Chaintreau</person>
<person>Pan Hui</person>
<person>Jon Crowcroft</person>
<person>Christophe Diot</person>
<person>Richard Gass</person>
<person>James Scott</person>
</author>
<title>Impact of Human Mobility on the Design of Opportunistic Forwarding Algorithms</title>
<booktitle>Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM)</booktitle>
<month>--04--</month>
<year>2006</year>
<address>Barcelona, Spain</address>
<url>http://www.cambridge.intel-research.net/haggle/pubs/</url>
<abstract>Studying transfer opportunities between wireless devices carried by humans, we 
observe that the distribution of the inter-contact time, that is the time gap 
separating two contacts of the same pair of devices, exhibits a heavy tail such 
as one of a power law, over a large range of value. This observation is 
confirmed on six distinct experimental data sets. It is at odds with the 
exponential decay implied by most mobility models. In this paper, we study how 
this new characteristic of human mobility impacts a class of previously 
proposed forwarding algorithms. We use a simplified model based on the renewal 
theory to study how the parameters of the distribution impact the delay 
performance of these algorithms. We make recommendation for the design of well 
founded opportunistic forwarding algorithms, in the context of human carried 
devices. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cambridge/haggle</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="39">
<key>chaintreau-pocket</key>
<techreport>
<author>
<person>Augustin Chaintreau</person>
<person>Pan Hui</person>
<person>Jon Crowcroft</person>
<person>Christophe Diot</person>
<person>Richard Gass</person>
<person>James Scott</person>
</author>
<title>Pocket Switched Networks, or Human mobility patterns as part of store-and-forward, or story-and-carry data transmission</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
<number>UCAM-CL-TR-617</number>
<month>--02--</month>
<year>2005</year>
<institution>University of Cambridge Computer Laboratory</institution>
<url>http://www.cl.cam.ac.uk/TechReports/UCAM-CL-TR-617.pdf</url>
<abstract>Opportunistic networks make use of human mobility and local forwarding in order 
to distribute data. Information can be stored and passed, taking advantage of 
the device mobility, or forwarded over a wireless link when an appropriate 
contact is met. Such networks fall into the fields of mobile ad-hoc networking 
and delay-tolerant networking. In order to evaluate forwarding algorithms for 
these networks, accurate data is needed on the intermittency of connections. 
\par In this paper, the inter-contact time between two transmission 
opportunities is observed empirically using four distinct sets of data, two 
having been specifically collected for this work, and two provided by other 
research groups. \par We discover that the distribution of inter-contact time 
follows an approximate power law over a large time range in all data sets. This 
observation is at odds with the exponential decay expected by many currently 
used mobility models. We demonstrate that opportunistic transmission schemes 
designed around these current models have poor performance under approximate 
power-law conditions, but could be significantly improved by using limited 
redundant transmissions. </abstract>
<category>wireless-meas,crawdad</category>
<refnames><refname>cambridge/haggle</refname>
</refnames>
</techreport>
<pubdate>20050201</pubdate>
</paper>

<paper id="40">
<key>chen-robust</key>
<article>
<author>
<person>Yilun Chen</person>
<person>Ami Wiesel</person>
<person>Alfred O. Hero III</person>
</author>
<title>Robust shrinkage estimation of high dimensional covariance matrices</title>
<journal>IEEE Transactions on Signal Processing</journal>
<pages>4097-4107</pages>
<publisher>IEEE</publisher>
<year>2011</year>
<volume>59</volume>
<number>9</number>
<month>Sep</month>
<url>http://arxiv.org/pdf/1009.5331</url>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>umich_rss</keywords>
<category>wireless-meas</category>
<refnames><refname>umich/rss</refname>
</refnames>
</article>
<pubdate>2011p01</pubdate>
</paper>

<paper id="41">
<key>cheng-cross-layer</key>
<inproceedings>
<author>
<person>Yu-Chung Cheng</person>
<person>Mikhail Afanasyev</person>
<person>Patrick Verkaik</person>
<person>P&#233;ter Benk&#246;</person>
<person>Jennifer Chiang</person>
<person>Alex C. Snoeren</person>
<person>Stefan Savage</person>
<person>Geoffrey M. Voelker</person>
</author>
<title>Automating cross-layer diagnosis of enterprise wireless networks</title>
<keywords>crawdad</keywords>
<keywords>ucsd/jigsaw</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>SIGCOMM '07: Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications</booktitle>
<year>2007</year>
<isbn>978-1-59593-713-1</isbn>
<pages>25-36</pages>
<address>Kyoto, Japan</address>
<doi>http://doi.acm.org/10.1145/1282380.1282384</doi>
<publisher>ACM</publisher>
<refnames><refname>ucsd/cse</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="42">
<key>cheng-cross-layer-journal</key>
<article>
<author>
<person>Yu-Chung Cheng</person>
<person>Mikhail Afanasyev</person>
<person>Patrick Verkaik</person>
<person>P&#233;ter Benk&#246;</person>
<person>Jennifer Chiang</person>
<person>Alex C. Snoeren</person>
<person>Stefan Savage</person>
<person>Geoffrey M. Voelker</person>
</author>
<title>Automating cross-layer diagnosis of enterprise wireless networks</title>
<keywords>crawdad</keywords>
<keywords>ucsd/jigsaw</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>SIGCOMM Comput. Commun. Rev.</journal>
<volume>37</volume>
<number>4</number>
<year>2007</year>
<issn>0146-4833</issn>
<pages>25-36</pages>
<doi>http://doi.acm.org/10.1145/1282427.1282384</doi>
<url>http://doi.acm.org/10.1145/1282427.1282384</url>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<refnames><refname>ucsd/cse</refname>
</refnames>
</article>
<pubdate>20070001</pubdate>
</paper>

<paper id="43">
<key>cheng-jigsaw</key>
<article>
<author>
<person>Yu-Chung Cheng</person>
<person>John Bellardo</person>
<person>P&#233;ter Benk&#246;</person>
<person>Alex C. Snoeren</person>
<person>Geoffrey M. Voelker</person>
<person>Stefan Savage</person>
</author>
<title>Jigsaw: solving the puzzle of enterprise 802.11 analysis</title>
<keywords>crawdad</keywords>
<keywords>ucsd/jigsaw</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>SIGCOMM Comput. Commun. Rev.</journal>
<volume>36</volume>
<number>4</number>
<year>2006</year>
<issn>0146-4833</issn>
<pages>39-50</pages>
<doi>http://doi.acm.org/10.1145/1151659.1159920</doi>
<url>http://doi.acm.org/10.1145/1151659.1159920</url>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<refnames><refname>ucsd/cse</refname>
</refnames>
</article>
<pubdate>20060001</pubdate>
</paper>

<paper id="44">
<key>cheng-metropolitan</key>
<inproceedings>
<author>
<person>Yu-Chung Cheng</person>
<person>Yatin Chawathe</person>
<person>Anthony LaMarca</person>
<person>John Krumm</person>
</author>
<title>Accuracy Characterization for Metropolitan-scale Wi-Fi Localization</title>
<booktitle>Proceedings of the Third International Conference on Mobile Systems, Applications, and Services</booktitle>
<year>2005</year>
<month>--06--</month>
<url>http://www.placelab.org/publications/pubs/pervasive-placelab-2005-final.pdf</url>
<abstract>Location systems have long been identified as an important component of 
emerging mobile applications. Most research on location systems has focused on 
precise location in indoor environments. However, many location applications 
(for example, location-aware web search) become interesting only when the 
underlying location system is available ubiquitously and is not limited to a 
single office environment. Unfortunately, the installation and calibration 
overhead involved for most of the existing research systems is too prohibitive 
to imagine deploying them across, say, an entire city. In this work, we 
evaluate the feasibility of building a wide-area 802.11 Wi-Fi-based positioning 
system. We compare a suite of wireless-radio-based positioning algorithms to 
understand how they can be adapted for such ubiquitous deployment with minimal 
calibration. In particular, we study the impact of this limited calibration on 
the accuracy of the positioning algorithms. Our experiments show that we can 
estimate a user's position with a median positioning error of 13-40 meters 
(depending upon the characteristics of the environment). Although this accuracy 
is lower than existing positioning systems, it requires substantially lower 
calibration overhead than existing indoor positioning systems and provides easy 
deployment and coverage across large metropolitan areas. Moreover, unlike GPS, 
it does not require line of sight to the sky and consequently works in areas 
where GPS does not (indoors and in dense urban environments). </abstract>
<category>mobile, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>intel_placelab</keywords>
<keywords>crawdad</keywords>
<refnames><refname>intel/placelab</refname>
</refnames>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="45">
<key>chinchilla-analysis</key>
<inproceedings>
<author>
<person>Francisco Chinchilla</person>
<person>Mark Lindsey</person>
<person>Maria Papadopouli</person>
</author>
<title>Analysis of wireless information locality and association patterns in a campus</title>
<booktitle>Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<pages>906-917</pages>
<month>--03--</month>
<year>2004</year>
<address>Hong Kong, China</address>
<publisher>IEEE</publisher>
<url>http://www.cs.unc.edu/~maria/infocom04.pdf</url>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>unc_campus</keywords>
<category>wireless-meas</category>
<refnames><refname>unc/campus</refname>
</refnames>
</inproceedings>
<pubdate>20040301</pubdate>
</paper>

<paper id="46">
<key>chon-evaluating</key>
<inproceedings>
<author>
<person>Yohan Chon</person>
<person>Hyojeong Shin</person>
<person>Elmurod Talipov</person>
<person>Hojung Cha</person>
</author>
<title>Evaluating mobility models for temporal prediction with high-granularity mobility data</title>
<booktitle>Proceedings of Pervasive Computing and Communications (PerCom)</booktitle>
<pages>206-212</pages>
<year>2012</year>
<series>PerCom'12</series>
<address>Lugano, Switzerland</address>
<url>http://mobed.yonsei.ac.kr/~yohan/Yohan_Chon_PerCom_2012.pdf</url>
<publisher>IEEE</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>yonsei_lifemap</keywords>
<category>wireless-meas</category>
<refnames><refname>yonsei/lifemap</refname>
</refnames>
</inproceedings>
<pubdate>20120001</pubdate>
</paper>

<paper id="47">
<key>chon-lifemap</key>
<article>
<author>
<person>Yohan Chon</person>
<person>Hojung Cha</person>
</author>
<title>LifeMap: A Smartphone-based Context Provider for Location-based Services</title>
<journal>IEEE Pervasive Computing</journal>
<year>2011</year>
<volume>10</volume>
<number>2</number>
<pages>58-67</pages>
<url>http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5686873</url>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>yonsei_lifemap</keywords>
<category>wireless-meas</category>
<refnames><refname>yonsei/lifemap</refname>
</refnames>
</article>
<pubdate>20110001</pubdate>
</paper>

<paper id="48">
<key>chon-mobility</key>
<inproceedings>
<author>
<person>Yohan Chon</person>
<person>Elmurod Talipov</person>
<person>Hyojeong Shin</person>
<person>Hojung Cha</person>
</author>
<title>Mobility prediction-based smartphone energy optimization for everyday location monitoring</title>
<booktitle>Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems</booktitle>
<pages>82-95</pages>
<year>2011</year>
<series>SenSys '11</series>
<address>New York, NY, USA</address>
<url>http://mobed.yonsei.ac.kr/~yohan/Yohan_Chon_SmartDC_SenSys_2011_Paper.pdf</url>
<publisher>ACM</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>yonsei_lifemap</keywords>
<category>wireless-meas</category>
<refnames><refname>yonsei/lifemap</refname>
</refnames>
</inproceedings>
<pubdate>20110001</pubdate>
</paper>

<paper id="49">
<key>claffy-community-wide</key>
<article>
<author><person>kc claffy</person>
</author>
<title>A day in the life of the internet": proposed community-wide experiment</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>SIGCOMM Computer Communication Review</journal>
<volume>36</volume>
<number>5</number>
<year>2006</year>
<month>--10--</month>
<issn>0146-4833</issn>
<pages>39-40</pages>
<url>http://doi.acm.org/10.1145/1163593.1163601</url>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
<category>crawdad</category>
</article>
<pubdate>20061001</pubdate>
</paper>

<paper id="50">
<key>claffy-conmi</key>
<article>
<author>
<person>kc claffy</person>
<person>Mark Crovella</person>
<person>Timur Friedman</person>
<person>Colleen Shannon</person>
<person>Neil Spring</person>
</author>
<title>Community-oriented network measurement infrastructure (CONMI) workshop report</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>SIGCOMM Computer Communication Review</journal>
<volume>36</volume>
<number>2</number>
<year>2006</year>
<issn>0146-4833</issn>
<pages>41-48</pages>
<url>http://doi.acm.org/10.1145/1129582.1129594</url>
<doi>http://doi.acm.org/10.1145/1129582.1129594</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
</article>
<pubdate>20060001</pubdate>
</paper>

<paper id="51">
<key>crawford-sanitzation</key>
<inproceedings>
<author>
<person>R. Crawford</person>
<person>M. Bishop</person>
<person>B. Bhumiratana</person>
<person>L. Clark</person>
<person>K. Levitt</person>
</author>
<title>Sanitization Models and their Limitations</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the New Security Paradigms Workshop</booktitle>
<mon>-09-</mon>
<year>2006</year>
<address>Schloss Dagstuhl,Germany</address>
<keyword>Data sanitization, inference problem, disclosure control, closed world assumption orld</keyword>
<abstract>This work explores issues of computational disclosure control. We examine 
assumptions in the foundations of traditional problem xamine statements and 
abstract models. We offer a comprehensive framework, based on the notion of an 
inference game, that unifies various inference problems by parameterizing their 
problem spaces. This work raises questions regarding the significance of 
intractability results. We analyze common structural aspects of inference 
problems via case studies; these emphasize why explicit policies are needed to 
specify all social context ethical values relevant to a problem instance. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="52">
<key>dahlberg-explorebots</key>
<inproceedings>
<author>
<person>Teresa Dahlberg</person>
<person>Asis Nasipuri</person>
<person>Craig Taylor</person>
</author>
<title>Explorebots: Mobile Network Experimentation</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-DahNas.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="53">
<key>daly-social</key>
<inproceedings>
<author>
<person>Elizabeth M. Daly</person>
<person>Mads Haahr</person>
</author>
<title>Social network analysis for routing in disconnected delay-tolerant MANETs</title>
<booktitle>MobiHoc '07: Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing</booktitle>
<year>2007</year>
<pages>32-40</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1288107.1288113</doi>
<url>http://doi.acm.org/10.1145/1288107.1288113</url>
<publisher>ACM Press</publisher>
<abstract>Message delivery in sparse Mobile Ad hoc Networks (MANETs) is difficult due to 
the fact that the network graph is rarely (if ever) connected. A key challenge 
is to find a route that can provide good delivery performance and low 
end-to-end delay in a disconnected network graph where nodes may move freely. 
This paper presents a multidisciplinary solution based on the consideration of 
the socalled small world dynamics which have been proposed for economy and 
social studies and have recently revealed to be a successful approach to be 
exploited for characterising information propagation in wireless networks. To 
this purpose, some bridge nodes are identified based on their centrality 
characteristics, i.e., on their capability to broker information exchange among 
otherwise disconnected nodes. Due to the complexity of the centrality metrics 
in populated networks the concept of ego networks is exploited where nodes are 
not required to exchange information about the entire network topology, but 
only locally available information is considered. Then SimBet Routing is 
proposed which exploits the exchange of pre-estimated â€˜betweennessâ€™ 
centrality metrics and locally determined social â€˜similarityâ€™ to the 
destination node. We present simulations using real trace data to demonstrate 
that SimBet Routing results in delivery performance close to Epidemic Routing 
but with significantly reduced overhead. Additionally, we show that Sim- Bet 
Routing outperforms PRoPHET Routing, particularly when the sending and 
receiving nodes have low connectivity. </abstract>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="54">
<key>dangerfield-evaluation</key>
<inproceedings>
<author>
<person>Ian Dangerfield</person>
<person>David Malone</person>
</author>
<title>Experimental Evaluation of 802.11e EDCA for Enhanced Voice over WLAN Performance</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/02-05.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="55">
<key>delmastro-experimental</key>
<inproceedings>
<author>
<person>Franca Delmastro</person>
<person>Eleonora Borgia</person>
<person>Marco Conti</person>
<person>Enrico Gregori</person>
</author>
<title>Experimental Comparison of Routing and Middleware Solutions for Mobile ad hoc Networks: Legacy vs. Cross-Layer Approach</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-DelBor.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="56">
<key>deshpande-sampling</key>
<inproceedings>
<author>
<person>Udayan Deshpande</person>
<person>Tristan Henderson</person>
<person>David Kotz</person>
</author>
<title>Channel Sampling Strategies for Monitoring Wireless Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<publisher>IEEE Computer Society Press</publisher>
<copyright>IEEE</copyright>
<url>http://www.cs.dartmouth.edu/~dfk/papers/deshpande:sampling.pdf</url>
<abstract>Monitoring the activity on an IEEE 802.11 network is useful for many 
applications, such as network management, optimizing deployment, or detecting 
network attacks. Deploying wireless sniffers to monitor every access point in 
an enterprise network, however, may be expensive or impractical. Moreover, some 
applications may require the deployment of multiple sniffers to monitor the 
numerous channels in an 802.11 network. In this paper, we explore sampling 
strategies for monitoring multiple channels in 802.11b/g networks. We describe 
a simple sampling strategy, where each channel is observed for an equal, 
predetermined length of time, and consider applications where such a strategy 
might be appropriate. We then introduce a sampling strategy that weights the 
time spent on each channel according to the number of frames observed on that 
channel, and compare the two strategies under experimental conditions. </abstract>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="57">
<key>doci-integratedtraffic</key>
<article>
<author>
<person>Arta Doci</person>
<person>Fatos Xhafa</person>
</author>
<title>WIT-Wireless Integrated Traffic</title>
<keywords>performance</keywords>
<keywords>traffic</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<journal>Mobile Information Systems</journal>
<year>2009</year>
<category>wireless-meas</category>
</article>
<pubdate>20090001</pubdate>
</paper>

<paper id="58">
<key>doci-mobility-tool</key>
<inproceedings>
<author><person>Arta Doci</person>
</author>
<title>Interconnected Traffic with Real Mobility Tool for Ad Hoc Networks</title>
<booktitle>Proceedings of the First International Workshop on Simulation and Modeling in Emergent Computational Systems (SMECS-2008)</booktitle>
<month>--09--</month>
<year>2008</year>
<address>Portland, Oregon, USA</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20080901</pubdate>
</paper>

<paper id="59">
<key>eagle-mobile-phones</key>
<misc>
<author><person>Nathan Eagle</person>
</author>
<title>Using Mobile Phones to Model Complex Social Systems</title>
<year>2005</year>
<month>--06--</month>
<category>crawdad</category>
<howpublished>O'Reilly Network</howpublished>
<url>http://www.oreillynet.com/pub/a/network/2005/06/20/MITmedialab.html</url>
<keyword>mobile, social sofware, networks, mit, location based</keyword>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>crawdad</keywords>
<refnames><refname>mit/reality</refname>
</refnames>
</misc>
<pubdate>20050601</pubdate>
</paper>

<paper id="60">
<key>eagle-reality</key>
<article>
<author>
<person>Nathan Eagle</person>
<person>Alex Pentland</person>
</author>
<title>Reality Mining: Sensing Complex Social Systems</title>
<journal>Journal of Personal and Ubiquitous Computing</journal>
<year>2005</year>
<url>http://reality.media.mit.edu/pdfs/realitymining.pdf</url>
<keyword>Bluetooth, Massachusetts Institute of Technology, mobile, mobile phone, telephone</keyword>
<abstract>We introduce a system for sensing complex social systems with data collected 
from one hundred mobile phones over the course of six months. We demonstrate 
the ability to use standard Bluetooth-enabled mobile telephones to measure 
information access and use in different contexts, recognize social patterns in 
daily user activity, infer relationships, identify socially significant 
locations, and model organizational rhythms. </abstract>
<category>wireless-meas, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>crawdad</keywords>
<refnames><refname>mit/reality</refname>
</refnames>
</article>
<pubdate>20050001</pubdate>
</paper>

<paper id="61">
<key>eisenman-ecsma</key>
<inproceedings>
<author>
<person>Shane B. Eisenman</person>
<person>Andrew T. Campbell</person>
</author>
<title>E-CSMA: Supporting Enhanced CSMA Performance in Experimental Sensor Networks using Per-neighbor Transmission Probability Thresholds</title>
<booktitle>Proceedings of the 26th IEEE International Conference on Computer Communications (INFOCOM)</booktitle>
<month>--05--</month>
<year>2007</year>
<address>Anchorage, AL</address>
<url>http://ieeexplore.ieee.org/iel5/4215581/4215582/04215726.pdf?tp=&amp;isnumber=&amp;arnumber=4215726</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>columbia_ecsma</keywords>
<keywords>crawdad</keywords>
<refnames><refname>columbia/ecsma</refname>
</refnames>
</inproceedings>
<pubdate>20070501</pubdate>
</paper>

<paper id="62">
<key>ergin-density</key>
<inproceedings>
<author>
<person>Mesut Ali Ergin</person>
<person>Kishore Ramachandran</person>
<person>Marco Gruteser</person>
</author>
<title>Understanding the effect of access point density on wireless LAN performance</title>
<booktitle>MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking</booktitle>
<year>2007</year>
<pages>350-353</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>rutgers_ap_density</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287853.1287902</doi>
<url>http://doi.acm.org/10.1145/1287853.1287902</url>
<publisher>ACM Press</publisher>
<abstract>In this paper, we present a systematic experimental study of the effect of 
inter-cell interference on IEEE 802.11 performance. With increasing penetration 
of WiFi into residential areas and usage in ad hoc conference settings, chaotic 
unplanned deployments are becoming the norm rather than an exception. These 
networks often operate many nearby access points and stations on the same 
channel, either due to lack of coordination or insufficient available channels. 
Thus, inter-cell interference is common but not well-understood. According to 
conventional wisdom, the efficiency of an 802.11 network is determined by the 
number of active clients. Surprisingly, we find that with a typical 
TCP-dominant workload, cumulative system throughput is characterized by the 
number of interfering access points rather than the number of clients. We find 
that due to TCP flow control, the number of backlogged stations in such a 
network equals twice the number of access points. Thus, a single access point 
network proved very robust even with over one hundred clients. Multiple 
interfering access points, however, lead to an increase in collisions that 
reduces throughput and affects volume of traffic in the network. </abstract>
<refnames><refname>rutgers/ap_density</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="63">
<key>faloutsos-repositories</key>
<article>
<author><person>Michalis Faloutsos</person>
</author>
<title>Public real data repositories and measurement tools</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>SIGCOMM Computer Communication Review</journal>
<volume>36</volume>
<number>2</number>
<year>2006</year>
<issn>0146-4833</issn>
<pages>37-40</pages>
<url>http://doi.acm.org/10.1145/1129582.1129593</url>
<doi>http://doi.acm.org/10.1145/1129582.1129593</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
</article>
<pubdate>20060001</pubdate>
</paper>

<paper id="64">
<key>felis-measurement</key>
<inproceedings>
<author>
<person>Sebastian Felis</person>
<person>Juergen Quittek</person>
<person>Lars Eggert</person>
</author>
<title>Measurement-Based Wireless LAN Troubleshooting</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Felis.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="65">
<key>feng-handoff</key>
<inproceedings>
<author>
<person>Fang Feng</person>
<person>Douglas S. Reeves</person>
</author>
<title>Explicit Proactive Handoff with Motion Prediction for Mobile IP</title>
<booktitle>Proceedings of the Wireless Communications and Networking Conference (WCNC)</booktitle>
<pages>855-860</pages>
<month>--03--</month>
<year>2004</year>
<volume>2</volume>
<publisher>IEEE Computer Society Press</publisher>
<url>http://ieeexplore.ieee.org/iel5/9178/29115/01311298.pdf?arnumber=1311298</url>
<abstract>Mobile IP has been widely accepted, but lacks a fast handoff mechanism. In this 
paper, we introduce an explicit proactive handoff scheme with motion 
prediction. Since each user has patterns of movement, a mobile node predicts 
its future motion and explicitly notifies its old foreign agent which subnet it 
is likely to handoff to. During a handoff, the old foreign agent duplicates and 
forwards packets to the predicted subnets. With our scheme, network-layer 
handoff latency can be reduced to the level of link-layer handoff latency, and 
the number of packets lost during handoffs is also minimized. With a real 
network activity trace, we demonstrate that this scheme is able to predict 
motion accurately, with only a small overhead in bandwidth consumption and 
computation. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth/campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20040301</pubdate>
</paper>

<paper id="66">
<key>fenner-stochastic</key>
<article>
<author><person>Fenner</person>
</author>
 T. and {Levene},
 M. and {Loizou},
 G. and {Roussos},
 G.},
<title>A Stochastic Evolutionary Growth Model for Social Networks</title>
<journal>ArXiv Physics e-prints</journal>
<month>--07--</month>
<year>2006</year>
<url>http://arxiv.org/abs/physics/0607188</url>
<category>wireless-meas, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</article>
<pubdate>20060701</pubdate>
</paper>

<paper id="67">
<key>ficek-intercall</key>
<inproceedings>
<author>
<person>Michal Ficek</person>
<person>Lukas Kencl</person>
</author>
<title>Inter-Call Mobility Model: A Spatio-temporal Refinement of Call Data Records Using a Gaussian Mixture Model</title>
<booktitle>The 31st Annual IEEE International Conference on Computer Communications (INFOCOM'2012)</booktitle>
<address>Orlando, Florida, USA</address>
<url>http://www.rdc.cz/download/publications/p469-ficek.pdf</url>
<month>--03--</month>
<year>2012</year>
<abstract>With global mobile phone penetration nearing 100\%, cellular Call Data Records 
(CDRs) provide a large-scale and ubiquitous, but also sparse and skewed 
snapshot of human mobility. It may be difficult or inappropriate to reach 
strong conclusions about user movement based on such data without proper 
understanding of user movement between call records. Based on an analysis of a 
real-world trace, we propose a novel, probabilistic Inter-Call Mobility (ICM) 
model of users' position in between calls. The ICM model combines Gaussian 
mixtures to build a general, comprehensive spatio-temporal refinement of CDRs. 
We demonstrate that ICM model's application yields strikingly different 
conclusions to the existing models when applied to basic CDR analyses, such as 
user proximity probability. </abstract>
<publisher>IEEE</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>ctu_personal</keywords>
<category>wireless-meas</category>
<refnames><refname>ctu/personal</refname>
</refnames>
</inproceedings>
<pubdate>20120301</pubdate>
</paper>

<paper id="68">
<key>ficek-spatial</key>
<inproceedings>
<author>
<person>Michal Ficek</person>
<person>Lukas Kencl</person>
</author>
<title>Spatial extension of the reality mining dataset</title>
<booktitle>IEEE 7th International Conference on Mobile Adhoc and Sensor Systems (MASS) 2010</booktitle>
<pages>666-673</pages>
<year>2010</year>
<address>San Francisco, CA</address>
<url>http://meltworks.org/MELT_Workshop/Program_files/ficek-kencl.pdf</url>
<month>--11--</month>
<publisher>IEEE</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>ctu_personal</keywords>
<category>wireless-meas</category>
<refnames><refname>ctu/personal</refname>
</refnames>
</inproceedings>
<pubdate>20101101</pubdate>
</paper>

<paper id="69">
<key>franceschinis-measuring</key>
<inproceedings>
<author>
<person>Mirko Franceschinis</person>
<person>Marco Mellia</person>
<person>Michela Meo</person>
<person>Maurizio Munafo</person>
</author>
<title>Measuring TCP over WiFi: A Real Case</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Franceschinis.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="70">
<key>gaertner-quality</key>
<article>
<author>
<person>Gregor Gaertner</person>
<person>Vinny Cahill</person>
</author>
<title>Understanding Link Quality in 802.11 Mobile Ad Hoc Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>IEEE Internet Computing</journal>
<pages>55-60</pages>
<month>--01--</month>
<year>2004</year>
<volume>8</volume>
<number>1</number>
<url>https://www.cs.tcd.ie/Gregor.Gaertner/UnderstandingLinkQuality.pdf</url>
<category>wireless-meas</category>
</article>
<pubdate>20040101</pubdate>
</paper>

<paper id="71">
<key>gaito-finegrained</key>
<inproceedings>
<author>
<person>Sabrina Gaito</person>
<person>Elena Pagani</person>
<person>Gian Paolo Rossi</person>
</author>
<title>Fine-Grained Tracking of Human Mobility in Dense Scenarios</title>
<booktitle>6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON) - Poster Session</booktitle>
<pages>40-42</pages>
<publisher>IEEE</publisher>
<year>2009</year>
<address>Roma (Italy)</address>
<month>--06--</month>
<url>http://homes.dico.unimi.it/~pagae/elena/articoli/abstract-secon09.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>unimi_pmtr</keywords>
<category>wireless-meas,crawdad</category>
<refnames><refname>unimi/pmtr</refname>
</refnames>
</inproceedings>
<pubdate>20090601</pubdate>
</paper>

<paper id="72">
<key>gaito-opportunistic</key>
<inproceedings>
<author>
<person>Sabrina Gaito</person>
<person>Elena Pagani</person>
<person>Gian Paolo Rossi</person>
</author>
<title>Opportunistic Forwarding in Workplaces</title>
<booktitle>Proceedings of 2nd ACM SIGCOMM Workshop on Online Social Networks</booktitle>
<pages>55-60</pages>
<year>2009</year>
<address>Barcelona, Spain</address>
<month>--08--</month>
<publisher>ACM</publisher>
<url>http://homes.dico.unimi.it/~pagae/elena/articoli/WOSN_09.pdf</url>
<abstract>So far, the search for Opportunistic Network (ON) applications has focused on 
urban/rural scenarios where the combined use of mobility and the 
store-carry-and-forward paradigm helpfully recovers from network partitions and 
copes with node sparsity. This paper explores the chance of using ONs in 
workplaces, where the node distribution is denser, thus contributing to reduce 
the message delivery latency, and where we still find similar needs for 
informal and unplanned network platforms to support human social relationships 
and interactions. Both a survey and trace recording experiments have been used 
to support the analysis of this mobility setting. The ability of recording very 
short contact times (i.e. lasting few seconds) allowed to interestingly show 
the slightly different role the social relationships play in dense scenarios 
and how the large amount of contacts (both short and long), occurring in 
densily populated spaces, actually contribute to reduce the message-delivery 
latency and to increase the delivery probability. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>unimi_pmtr</keywords>
<keywords>crawdad</keywords>
<category>wireless-meas,crawdad</category>
<refnames><refname>unimi/pmtr</refname>
</refnames>
</inproceedings>
<pubdate>20090801</pubdate>
</paper>

<paper id="73">
<key>ganu-capture</key>
<inproceedings>
<author>
<person>Sachin Ganu</person>
<person>Kishore Ramachandran</person>
<person>Marco Gruteser</person>
<person>Ivan Seskar</person>
<person>Jing Deng</person>
</author>
<title>Methods for restoring MAC layer fairness in IEEE 802.11 networks with physical layer capture</title>
<booktitle>REALMAN '06: Proceedings of the second international workshop on Multi-hop ad hoc networks: from theory to reality</booktitle>
<year>2006</year>
<pages>7-14</pages>
<doi>http://doi.acm.org/10.1145/1132983.1132986</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
<url>http://doi.acm.org/10.1145/1132983.1132986</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>rutgers_capture</keywords>
<keywords>crawdad</keywords>
<refnames><refname>rutgers/capture</refname>
</refnames>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="74">
<key>gass-in-motion</key>
<inproceedings>
<author>
<person>Richard Gass</person>
<person>James Scott</person>
<person>Christophe Diot</person>
</author>
<title>Measurements of In-Motion 802.11 Networking</title>
<booktitle>Proceedings of the 7th IEEE Workshop on Mobile Computing Systems and Applications</booktitle>
<month>--04--</month>
<year>2006</year>
<pages>69-74</pages>
<url>http://dx.doi.org/10.1109/WMCSA.2006.14</url>
<address>Semiahmoo Resort, Washington, USA</address>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_inmotion</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cambridge/inmotion</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="75">
<key>gass-in-motion-tr</key>
<techreport>
<author>
<person>Richard Gass</person>
<person>James Scott</person>
<person>Christophe Diot</person>
</author>
<title>Measurements of In-Motion 802.11 Networking</title>
<number>IRC-TR-05-050</number>
<month>--10--</month>
<year>2005</year>
<institution>Intel Research Technical Report</institution>
<url>http://www.pittsburgh.intel-research.net/~rgass/papers/tr/irc-tr05050-inmotion.pdf</url>
<category>crawdad</category>
<abstract>Wireless networking can support in-motion users by providing occasional 
opportunities to transmit and receive data. We measure the performance of UDP 
and TCP transfers between a car traveling at speeds from 5 mph to 75 mph, and 
an 802.11b access point. We analyze the impact of bandwidth and delay 
limitations in the backhaul network on the feasibility of in-motion transfer 
with typical Internet applications. We observe that in interference-free 
environments, a significant amount of data can be transferred using 
off-the-shelf equipment. We find that performance suffers mostly from network 
or application related problems instead of wireless link issues, i.e., 
protocols with handshakes, bandwidth limitations, and long round-trip times. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_inmotion</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cambridge/inmotion</refname>
</refnames>
</techreport>
<pubdate>20051001</pubdate>
</paper>

<paper id="76">
<key>ghosh-profiling</key>
<techreport>
<author>
<person>Joy Ghosh</person>
<person>Matthew J. Beal</person>
<person>Hung Q. Ngo</person>
<person>Chunming Qiao</person>
</author>
<title>On Profiling Mobility and Predicting Locations of Campus-wide Wireless Network Users</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<month>--12--</month>
<year>2005</year>
<institution>Department of Computer Science and Engineering University at Buffalo, The State University of New York</institution>
<url>http://www.cse.buffalo.edu/tech-reports/2005-27.pdf</url>
<abstract>In this paper, we analyze a year long wireless network users' mobility trace 
data collected on ETH Zurich campus. Unlike earlier work, we profile the 
movement pattern of wireless users and predict their locations. More 
specifically, we show that each network user regularly visits a list of places, 
such as a building (also referred to as "hubs") with some probability. The 
daily list of hubs, along with their corresponding visit probabilities, are 
referred to as a mobility profile. We also show that over a period of time 
(e.g., a week), a user may repeatedly follow a mixture of mobility profiles 
with certain probabilities associated with each of the profiles. Our analysis 
of the mobility trace data not only validate the existence of our so-called 
sociological orbits, but also demonstrate the advantages of exploiting it in 
performing hub-level location predictions. Moreover, such profile based 
location predictions are found not only to be more precise than a common 
statistical approach based on observed hub visitation frequencies, but also 
shown to incur a much lower overhead. We further illustrate the benefit of 
profiling users' mobility by discussing relevant work and suggesting 
applications in different types of wireless networks, including mobile ad hoc 
networks. </abstract>
<category>wireless-meas</category>
</techreport>
<pubdate>20051201</pubdate>
</paper>

<paper id="77">
<key>gonzalez-hams</key>
<inproceedings>
<author>
<person>Francisco Gonz&#225;lez</person>
<person>Jes&#250;s A. P&#233;rez</person>
<person>Victor H. Z&#225;rate</person>
</author>
<title>HAMS: Layer 2 Handoff Accurate Measurement Strategy in WLANs 802.11</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Gonzalez.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="78">
<key>gopal-evaluation</key>
<inproceedings>
<author>
<person>Sumathi Gopal</person>
<person>Dipankar Raychaudhuri</person>
</author>
<title>Experimental Evaluation of the TCP Simultaneous Send Problem in 802.11 Wireless Local Area Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-GopRay.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="79">
<key>gorlatova-networking</key>
<inproceedings>
<author>
<person>Maria Gorlatova</person>
<person>Aya Wallwater</person>
<person>Gil Zussman</person>
</author>
<title>Networking Low-Power Energy Harvesting Devices: Measurements and Algorithms</title>
<booktitle>IEEE Computer Communications Conference (IEEE INFOCOM'11)</booktitle>
<year>2011</year>
<month>--04--</month>
<publisher>IEEE</publisher>
<address>Shanghai, China</address>
<url>http://enhants.ee.columbia.edu/images/CU-EE-2010-07-15a.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>columbia_enhants</keywords>
<category>wireless-meas, crawdad</category>
<refnames><refname>columbia/enhants</refname>
</refnames>
</inproceedings>
<pubdate>20110401</pubdate>
</paper>

<paper id="80">
<key>gray-outdoor</key>
<inproceedings>
<author>
<person>Robert S. Gray</person>
<person>David Kotz</person>
<person>Calvin Newport</person>
<person>Nikita Dubrovsky</person>
<person>Aaron Fiske</person>
<person>Jason Liu</person>
<person>Christopher Masone</person>
<person>Susan McGrath</person>
<person>Yougu Yuan</person>
</author>
<title>Outdoor Experimental Comparison of Four Ad Hoc Routing Algorithms</title>
<booktitle>Proceedings of the ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)</booktitle>
<year>2004</year>
<month>--10--</month>
<pages>220-229</pages>
<publisher>ACM Press</publisher>
<copyright>ACM</copyright>
<note>Finalist for Best Paper award</note>
<url>http://www.cs.dartmouth.edu/~dfk/papers/gray:compare.pdf</url>
<keyword>wireless network, mobile computing, ad hoc network, dfk, MANET</keyword>
<abstract>Most comparisons of wireless ad hoc routing algorithms involve simulated or \em 
indoor trial runs, or outdoor runs with only a small number of nodes, 
potentially leading to an incorrect picture of algorithm performance. In this 
paper, we report on an outdoor comparison of four different routing algorithms, 
APRL, AODV, ODMRP, and STARA, running on top of thirty-three 802.11-enabled 
laptops moving randomly through an athletic field. This comparison provides 
insight into the behavior of ad hoc routing algorithms at larger real-world 
scales than have been considered so far. In addition, we compare the outdoor 
results with both indoor (``tabletop'') and simulation results for the same 
algorithms, examining the differences between the indoor results and the 
outdoor reality. Finally, we describe the software infrastructure that allowed 
us to implement the ad hoc routing algorithms in a comparable way, and use the 
\em same codebase for indoor, outdoor, and simulated trial runs. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_outdoor</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/outdoor</refname>
</refnames>
</inproceedings>
<pubdate>20041001</pubdate>
</paper>

<paper id="81">
<key>gronvall-voice</key>
<inproceedings>
<author>
<person>Bj&#246;rn Gr&#246;nvall</person>
<person>Ian Marsh</person>
</author>
<title>Performance Evaluation of Voice Handovers in Real 802.11 Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/02-04.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="82">
<key>gwon-experimental</key>
<inproceedings>
<author>
<person>Youngjune Gwon</person>
<person>James Kempf</person>
<person>Raghu Dendukuri</person>
<person>Ravi Jain</person>
</author>
<title>Experimental Results on IP-layer Enhancement to Capacity of VoIPv6 over IEEE 802.11b Wireless LAN</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Gwon.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="83">
<key>hadaller-multi-vehicular</key>
<inproceedings>
<author>
<person>David Hadaller</person>
<person>Srinivasan Keshav</person>
<person>Tim Brecht</person>
</author>
<title>MV-MAX: Improving Wireless Infrastructure Access for Multi-Vehicular Communication</title>
<booktitle>Proceedings of the ACM SIGCOMM Workshop on Challenged Networks (CHANTS 2006)</booktitle>
<address>Pisa, Italy</address>
<month>--09--</month>
<year>2006</year>
<url>http://www.cs.uwaterloo.ca/~dthadall/research/papers/MV-MAX-SIGCOMM_CHANTS06-Paper.pdf</url>
<abstract>When a roadside 802.11-based wireless access point is shared by more than one 
vehicle, the vehicle with the lowest transmission rate reduces the effective 
transmission rate of all other vehicles. This performance anomaly degrades both 
individual and overall throughput in such multi-vehicular environments. 
Observing that every vehicle eventually receives good performance when it is 
near the access point, we propose MV-MAX (Multi-Vehicular Maximum), a medium 
access protocol that opportunistically grants wireless access to vehicles with 
the maximum transmission rate. Mathematical analysis and trace-driven 
simulations based on real data show that MV-MAX not only improves overall 
system throughput, compared to 802.11, by a factor of almost 4, but also 
improves on the previously proposed time-fairness scheme by a factor of more 
than 2. Moreover, despite being less fair than 802.11, almost every vehicle 
benefits by using MV-MAX over the more equitable 802.11 access mechanism. 
Finally, we show that our results are consistent across different data sets. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_inmotion</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060901</pubdate>
</paper>

<paper id="84">
<key>han-wibro</key>
<inproceedings>
<author>
<person>Mongnam Han</person>
<person>Youngseok Lee</person>
<person>Sue Moon</person>
<person>Keon Jang</person>
<person>Dooyoung Lee</person>
</author>
<title>Evaluation of VoIP Quality over WiBro</title>
<booktitle>PAM 2008, 9th Passive and Active Measurement conference</booktitle>
<year>2008</year>
<month>--04--</month>
<pages>51-60</pages>
<url>http://an.kaist.ac.kr/~sbmoon/paper/intl-conf/2008-pam-wibro.pdf</url>
<address>Cleveland, Ohio</address>
<abstract>In this work, we have conducted experiments to evaluate QoS of VoIP 
applications over the WiBro network. In order to capture the baseline 
performance of the WiBro network we measure and analyze the characteristics of 
delay and throughput under stationary and mobile scenarios. Then we evaluate 
QoS of VoIP applications using the E-Model of ITU-T G.107. Our measurements 
show that the achievable maximum throughputs are 5.3 Mbps in downlink and 2 
Mbps in uplink. VoIP quality is better than or at least as good as toll quality 
despite user mobility exceeding the protected limit of WiBro mobility support. 
Using RAS and sector identification information, we show that the handoff is 
correlated with throughput and quality degradation. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>kaist_wibro</keywords>
<keywords>crawdad</keywords>
<refnames><refname>kaist/wibro</refname>
</refnames>
</inproceedings>
<pubdate>20080401</pubdate>
</paper>

<paper id="85">
<key>henderson-changing</key>
<article>
<author>
<person>Henderson, Tristan</person>
<person>Kotz, David</person>
<person>Abyzov, Ilya</person>
</author>
<title>The Changing Usage of a Mature Campus-wide Wireless Network</title>
citeulike-article-id={2902063},
<doi>10.1016/j.comnet.2008.05.003</doi>
<journal>Computer Networks</journal>
<keywords>80211</keywords>
<keywords>crawdad</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>measurement</keywords>
<keywords>mobility</keywords>
<keywords>network-measurement</keywords>
<keywords>wireless</keywords>
<keywords>wireless-lan</keywords>
posted-at = {2008-06-17 12:13:10},
<url>http://dx.doi.org/10.1016/j.comnet.2008.05.003</url>
<volume>In Press, Accepted Manuscript</volume>
<refnames><refname>dartmouth/campus</refname>
</refnames>
</article>
<pubdate>00000001</pubdate>
</paper>

<paper id="86">
<key>henderson-esm</key>
<inproceedings>
<author>
<person>Tristan Henderson</person>
<person>Denise Anthony</person>
<person>David Kotz</person>
</author>
<title>Measuring wireless network usage with the Experience Sampling Method</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers//WiNMee_Henderson.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="87">
<key>henderson-measuring</key>
<inproceedings>
<author>
<person>Tristan Henderson</person>
<person>David Kotz</person>
</author>
<title>Measuring Wireless LANs</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<marknew>changed</marknew>
<booktitle>Mobile, Wireless and Sensor Networks: Technology, Applications and Future Directions</booktitle>
<editor>Rajeev Shorey et al.</editor>
<publisher>John Wiley &amp; Sons</publisher>
<copyright>John Wiley &amp; Sons</copyright>
<address>New York, NY</address>
<year>2006</year>
<pages>5-27</pages>
<chapter>1</chapter>
<vitatype>invchapter</vitatype>
<group>cmc,dfk</group>
<category>wireless</category>
<keyword>wireless network, measurement, dfk</keyword>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="88">
<key>henderson-voice</key>
<inproceedings>
<author>
<person>Tristan Henderson</person>
<person>David Kotz</person>
<person>Ilya Abyzov</person>
</author>
<title>The Changing Usage of a Mature Campus-wide Wireless Network</title>
<booktitle>Proceedings of the Tenth Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<pages>187-201</pages>
<month>--09--</month>
<year>2004</year>
<address>Philadelphia, PA, USA</address>
<publisher>ACM Press</publisher>
<url>http://www.cs.dartmouth.edu/~dfk/papers/henderson:voice.pdf</url>
<keyword>mobile computing, wireless network, workload characterization, voice over IP, VoIP, P2P</keyword>
<category>wireless-meas,wireless,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/campus</refname>
</refnames>
</inproceedings>
<pubdate>20040901</pubdate>
</paper>

<paper id="89">
<key>hernandez-assessing</key>
<inproceedings>
<author>
<person>Felix Hernandez-Campos</person>
<person>Maria Papadopouli</person>
</author>
<title>Assessing The Real Impact of 802.11 WLANs: A Large-Scale Comparison of Wired and Wireless Traffic</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 14th IEEE Workshop on Local and Metropolitan Area Networks</booktitle>
<month>--09--</month>
<year>2005</year>
<address>Crete, Greece</address>
<url>http://www.cs.unc.edu/~maria/lanman05-B.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050901</pubdate>
</paper>

<paper id="90">
<key>hernandez-comp</key>
<inproceedings>
<author>
<person>Felix Hernandez-Campos</person>
<person>Maria Papadopouli</person>
</author>
<title>A Comparative Measurement Study of the Workload of Wireless Access Points in Campus Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 16th Annual IEEE International Symposium on Personal Indoor and Mobile Radio Communications</booktitle>
<month>--09--</month>
<year>2005</year>
<address>Berlin, Germany</address>
<url>http://www.cs.unc.edu/~maria/pimrc05-B.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050901</pubdate>
</paper>

<paper id="91">
<key>hilal-interactions</key>
<inproceedings>
<author>
<person>A. Hilal</person>
<person>J. N. Chattha</person>
<person>V. Srivastava</person>
<person>M. S. Thompson</person>
<person>A. B. MacKenzie</person>
<person>L. A. DaSilva</person>
</author>
<title>Interactions Between Cooperation Strategies in Mobile Ad Hoc Networks</title>
<year>2008</year>
<booktitle>Proceedings of the Third ACM International Workshop on Wireless Network Testbeds, Experimental evaluation and CHaracterization (WiNTECH)</booktitle>
<address>San Francisco, CA</address>
<month>--09--</month>
<url>http://www.maniacchallenge.org/demofinal.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>vt_maniac</keywords>
<keywords>crawdad</keywords>
<refnames><refname>vt/maniac</refname>
</refnames>
<abstract>Cooperation among nodes in an ad hoc network is essential for multi-hop 
communication. Non- cooperative or selfish nodes reduce (or cease) cooperation 
by refusing to forward packets for others. In this demo we showcase the 
interactions between various cooperation strategies and quantify their impact 
on timely delivery of traffic across multi-hop routes. The cooperation 
strategies are implemented under the Linux operating system and run on an ad 
hoc network composed of virtual nodes on multiple physical workstations. The 
demo includes an interactive component that allows the audience to select the 
cooperation strategy to run on each individual network node and observe the 
effects of the selected combination of strategies on network performance. The 
mobility between nodes is emulated from connectivity traces gathered at the 
2007 MANIAC Challenge. </abstract>
</inproceedings>
<pubdate>20080901</pubdate>
</paper>

<paper id="92">
<key>hoffbeck-rf</key>
<inproceedings>
<author><person>Joseph Hoffbeck</person>
</author>
<title>RF Signal Database for a Communication Systems Course</title>
<booktitle>Proceedings of American Society for Engineering Education Annual Conference and Exposition (ASEE 2006)</booktitle>
<month>--06--</month>
<year>2006</year>
<address>Chicago, IL, USA</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>up_rf_recordings</keywords>
<keywords>crawdad</keywords>
<refnames><refname>up/rf_recordings</refname>
</refnames>
</inproceedings>
<pubdate>20060601</pubdate>
</paper>

<paper id="93">
<key>hsu-associations</key>
<inproceedings>
<author>
<person>Wei-Jen Hsu</person>
<person>Ahmed Helmy</person>
</author>
<title>On Modeling User Associations in Wireless LAN Traces on University Campuses</title>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/01-05.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>ibm_watson</keywords>
<keywords>crawdad</keywords>
<refnames><refname>usc/mobilib</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="94">
<key>hsu-behavioral-groups</key>
<inproceedings>
<author>
<person>Wei-jen Hsu</person>
<person>Debojyoti Dutta</person>
<person>Ahmed Helmy</person>
</author>
<title>Mining behavioral groups in large wireless LANs</title>
<booktitle>MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking</booktitle>
<year>2007</year>
<pages>338-341</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287853.1287899</doi>
<url>http://doi.acm.org/10.1145/1287853.1287899</url>
<publisher>ACM Press</publisher>
<abstract>Recent years have witnessed significant growth in the adoption of portable 
wireless communication and computing devices (e.g., laptops, PDAs, smart 
phones) and large-scale deployment of wireless networks (e.g., cellular, 
WLANs). We envision that future usage of mobile devices and services will be 
highly personalized. Users will incorporate these new technologies into their 
daily lives, and the way they use new devices and services will reflect their 
personality and lifestyle. Therefore it is imperative to study and characterize 
the fundamental structure of wireless user behavior in order to model, manage, 
leverage and design efficient mobile networks and services. In this study, 
using our systematic TRACE approach, we analyze wireless users' behavioral 
patterns by extensively mining wireless network logs from two major university 
campuses. We represent the data using location-preference vectors, and utilize 
unsupervised learning (clustering) to classify trends in user behavior using 
novel similarity metrics. Matrix decomposition techniques are used to identify 
(and differentiate between) major patterns. We discover multi-modal user 
behavior and hundreds of distinct groups with unique behavioral patterns in 
both campuses, and their sizes follow a power-law distribution. Our methods and 
findings might provide new directions in network management and behavior-aware 
network protocols and applications, to name a few. </abstract>
<refnames><refname>usc/mobilib</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="95">
<key>hsu-impact</key>
<techreport>
<author>
<person>Wei-jen Hsu</person>
<person>Ahmed Helmy</person>
</author>
<title>IMPACT: Investigation of Mobile-user Patterns Across University Campuses using WLAN Trace Analysis</title>
<month>--07--</month>
<year>2005</year>
<institution>Electrical Engineering Department, University of Southern California</institution>
<url>http://nile.usc.edu/MobiLib/Trace_analysis_TR.pdf</url>
<abstract>We conduct the most comprehensive study of WLAN traces to date. Measurements 
collected from four major university campuses are analyzed with the aim of 
developing fundamental understanding of realistic user behavior in wireless 
networks. Both individual user and inter-node (group) behaviors are 
investigated and two classes of metrics are devised to capture the underlying 
structure of such behaviors. For individual user behavior we observe distinct 
patterns in which most users are 'on' for a small fraction of the time, the 
number of access points visited is very small and the overall online user 
mobility is quite low. We clearly identify categories of heavy and light users. 
In general, users exhibit high degree of similarity over days and weeks. For 
group behavior, we define metrics for encounter patterns and friendship. 
Surprisingly, we find that a user, on average, encounters less than 6\% of the 
network user population within a month, and that encounter and friendship 
relations are highly asymmetric. We establish that number of encounters follows 
a biPareto distribution, while friendship indexes follow an exponential 
distribution. We capture the encounter graph using a small world model, the 
characteristics of which reach steady state after only one day. We hope for our 
study to have a great impact on realistic modeling of network usage and 
mobility patterns in wireless networks. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>ibm_watson</keywords>
<keywords>crawdad</keywords>
<refnames><refname>usc/mobilib</refname>
</refnames>
</techreport>
<pubdate>20050701</pubdate>
</paper>

<paper id="96">
<key>hsu-mobility</key>
<inproceedings>
<author>
<person>Wei-jen Hsu</person>
<person>Thrasyvoulos Spyropoulos</person>
<person>Konstantinos Psounis</person>
<person>Ahmed Helmy</person>
</author>
<title>Modeling Time-variant User Mobility in Wireless Mobile Networks</title>
<booktitle>Proceedings of the 26th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<month>--03--</month>
<year>2007</year>
<address>Anchorage, Alaska</address>
<publisher>IEEE</publisher>
<url>http://nile.cise.ufl.edu/~weijenhs/publication/INFOCOM_camera_final.pdf</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>ibm_watson</keywords>
<keywords>crawdad</keywords>
<refnames><refname>usc/mobilib</refname>
</refnames>
</inproceedings>
<pubdate>20070301</pubdate>
</paper>

<paper id="97">
<key>hsu-nodal</key>
<inproceedings>
<author>
<person>Wei-Jen Hsu</person>
<person>Ahmed Helmy</person>
</author>
<title>On Nodal Encounter Patterns in Wireless LAN Traces</title>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/02-03.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>ibm_watson</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
<refnames><refname>usc/mobilib</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="98">
<key>hsu-profile-cast</key>
<article>
<author>
<person>Wei-jen Hsu</person>
<person>Debojyoti Dutta</person>
<person>Ahmed Helmy</person>
</author>
<title>Profile-cast: behavior-aware mobile networking</title>
<journal>SIGMOBILE Mob. Comput. Commun. Rev.</journal>
<keywords>80211</keywords>
<keywords>crawdad</keywords>
<keywords>usc_mobilib</keywords>
<keywords>measurement</keywords>
<keywords>mobility</keywords>
<keywords>network-measurement</keywords>
<keywords>wireless</keywords>
<keywords>wireless-lan</keywords>
<volume>12</volume>
<number>1</number>
<year>2008</year>
<issn>1559-1662</issn>
<pages>52-54</pages>
<url>http://doi.acm.org/10.1145/1374512.1374529</url>
<doi>http://doi.acm.org/10.1145/1374512.1374529</doi>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<refnames><refname>usc/mobilib</refname>
</refnames>
</article>
<pubdate>20080001</pubdate>
</paper>

<paper id="99">
<key>hsu-structure-poster</key>
<misc>
<author>
<person>Weijen Hsu</person>
<person>Debojyoti Dutta</person>
<person>Ahmed Helmy</person>
</author>
<title>MobiCom Poster: On the Structure of User Association Patterns in Wireless LANs</title>
<year>2006</year>
<month>--09--</month>
<category>crawdad</category>
<howpublished>Poster presentation at MobiCom 2006</howpublished>
<url>http://portal.acm.org/citation.cfm?id=1282239</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<refnames><refname>usc/mobilib</refname>
</refnames>
</misc>
<pubdate>20060901</pubdate>
</paper>

<paper id="100">
<key>hui-bubble</key>
<techreport>
<author>
<person>Pan Hui</person>
<person>Jon Crowcroft</person>
</author>
<title>Bubble Rap: Forwarding in small world DTNs in ever decreasing circles</title>
<number>UCAM-CL-TR-684</number>
<month>--05--</month>
<year>2007</year>
<institution>University of Cambridge Computer Laboratory</institution>
<url>http://www.cl.cam.ac.uk/TechReports/UCAM-CL-TR-684.pdf</url>
<abstract>In this paper we seek to improve understanding of the structure of human 
mobility, and to use this in the design of forwarding algorithms for Delay 
Tolerant Networks for the dissemination of data amongst mobile users. 
Cooperation binds but also divides human society into communities. Members of 
the same community interact with each other preferentially. There is structure 
in human society. Within society and its communities, individuals have varying 
popularity. Some people are more popular and interact with more people than 
others; we may call them hubs. Popularity ranking is one facet of the 
population. In many physical networks, some nodes are more highly connected to 
each other than to the rest of the network. The set of such nodes are usually 
called clusters, communities, cohesive groups or modules. There is structure to 
social networking. Different metrics can be used such as information flow, 
Freeman betweenness, closeness and inference power, but for all of them, each 
node in the network can be assigned a global centrality value. What can be 
inferred about individual popularity, and the structure of human society from 
measurements within a network? How can the local and global characteristics of 
the network be used practically for information dissemination? We present and 
evaluate a sequence of designs for forwarding algorithms for Pocket Switched 
Networks, culminating in Bubble, which exploit increasing levels of information 
about mobility and interaction. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>mit_reality</keywords>
<keywords>upmc_content</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cambridge/haggle</refname>
<refname>upmc/content</refname>
</refnames>
</techreport>
<pubdate>20070501</pubdate>
</paper>

<paper id="101">
<key>hui-community</key>
<inproceedings>
<author>
<person>Pan Hui</person>
<person>Eiko Yoneki</person>
<person>Shu-yan Chan</person>
<person>Jon Crowcroft</person>
</author>
<title>Distributed Community Detection in Delay Tolerant Networks</title>
<booktitle>Proceedings of the ACM SIGCOMM MobiArch Workshop</booktitle>
<month>--08--</month>
<year>2007</year>
<address>Kyoto, Japan</address>
<url>http://www.cl.cam.ac.uk/~ph315/publications/mobiarch.pdf</url>
<abstract>Community is an important attribute of Pocket Switched Networks (PSN), because 
mobile devices are carried by people who tend to belong to communities. We 
analysed community structure from mobility traces and used for forwarding 
algorithms [12], which shows significant impact of community. Here, we propose 
and evaluate three novel distributed community detection approaches with great 
potential to detect both static and temporal communities. We find that with 
suitable configuration of the threshold values, the distributed community 
detection can approximate their corresponding centralised methods up to 90% 
accuracy. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>upmc_content</keywords>
<keywords>crawdad</keywords>
<refnames><refname>upmc/content</refname>
</refnames>
</inproceedings>
<pubdate>20070801</pubdate>
</paper>

<paper id="102">
<key>hui-conference</key>
<inproceedings>
<author>
<person>Pan Hui</person>
<person>Augustin Chaintreau</person>
<person>James Scott</person>
<person>Richard Gass</person>
<person>Jon Crowcroft</person>
<person>Christophe Diot</person>
</author>
<title>Pocket Switched Networks and Human Mobility in Conference Environments</title>
<booktitle>Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking</booktitle>
<month>--08--</month>
<year>2005</year>
<pages>244-251</pages>
<address>Philadelphia, PA, USA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-HuiCha.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cambridge/haggle</refname>
</refnames>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="103">
<key>hutchins-wireless</key>
<inproceedings>
<author>
<person>Ron Hutchins</person>
<person>Ellen W. Zegura</person>
</author>
<title>Measurements From a Campus Wireless Network</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the IEEE International Conference on Communications (ICC)</booktitle>
<pages>3161-3167</pages>
<month>--04--</month>
<year>2002</year>
<volume>5</volume>
<address>New York</address>
<publisher>IEEE Computer Society Press</publisher>
<url>http://www.cc.gatech.edu/computing/Telecomm/seminar/fall01/wireless.pdf</url>
<keyword>mobile computing, wireless network, workload characterization</keyword>
<abstract>In this paper we examine a high speed wireless access network and present 
traffic patterns and on-line behavior for wireless users. To date, wireless 
network studies have largely focused on cellular voice technologies and 
architectures. Here we present an analysis of data collected from an 
authenticated campus area access network providing both wireless 802.11b and 
walk-up Ethernet capabilities through an authenticated access network service. 
We present an analysis of session data, transport layer flow data, and movement 
data taken from 109 wireless access points spread across 18 buildings. Local 
Area Wireless Network (LAWN) wireless services support about 444 wireless 
hosts, 765 current users, and have sustained more than a million TCP flows over 
the nearly two month collection period. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20020401</pubdate>
</paper>

<paper id="104">
<key>iqbal-srvf</key>
<inproceedings>
<author>
<person>Adnan Iqbal</person>
<person>M. Khurram Shahzad</person>
<person>Syed Ali Khayam</person>
</author>
<title>SRVF: An Energy-Efficient Link Layer Protocol for Reliable Transmission over Wireless Sensor Networks</title>
<keywords>crawdad</keywords>
<keywords>niit_bit_errors</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the IEEE International Conference on Communications (ICC)</booktitle>
<pages>146-150</pages>
<month>--05--</month>
<year>2008</year>
<address>New York</address>
<publisher>IEEE Computer Society Press</publisher>
<url>http://www.niit.edu.pk/~khayam/pdf/2008/icc08_srvf.pdf</url>
<refnames><refname>niit/bit_errors</refname>
</refnames>
</inproceedings>
<pubdate>20080501</pubdate>
</paper>

<paper id="105">
<key>iqbal-two-tier</key>
<inproceedings>
<author>
<person>Adnan Iqbal</person>
<person>Syed Ali Khayam</person>
</author>
<title>Improving WSN Simulation and Analysis Accuracy Using Two-Tier Channel Models</title>
<keywords>crawdad</keywords>
<keywords>niit_bit_errors</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the IEEE International Conference on Communications (ICC)</booktitle>
<pages>349-353</pages>
<month>--05--</month>
<year>2008</year>
<address>New York</address>
<publisher>IEEE Computer Society Press</publisher>
<url>http://www.niit.edu.pk/~khayam/pdf/2008/icc08_simulation.pdf</url>
<refnames><refname>niit/bit_errors</refname>
</refnames>
</inproceedings>
<pubdate>20080501</pubdate>
</paper>

<paper id="106">
<key>ireland-long-distance</key>
<inproceedings>
<author>
<person>Timothy Ireland</person>
<person>Adam Nyzio</person>
<person>Michael Zink</person>
<person>Jim Kurose</person>
</author>
<title>The Impact of Directional Antenna Orientation, Spacing, and Channel Separation on Long-distance Multi-hop 802.11g Networks: A Measurement Study</title>
<booktitle>Proceedings of the Third Workshop on Wireless Network Measurements (WiNMee 2007)</booktitle>
<month>--04--</month>
<year>2007</year>
<address>Limassol, Cyprus, Cyprus</address>
<url>http://skuld.cs.umass.edu/traces/wireless_traces/WiNMee07.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_long_distance</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umass/long_distance</refname>
</refnames>
</inproceedings>
<pubdate>20070401</pubdate>
</paper>

<paper id="107">
<key>jadhav-lessons</key>
<inproceedings>
<author>
<person>Sushant Jadhav</person>
<person>Timothy Brown</person>
<person>Sheetalkumar Doshi</person>
<person>Daniel Henkel</person>
<person>Roshan Thekkekunnel</person>
</author>
<title>Lessons Learned Constructing A Wireless Ad Hoc Network Test Bed</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Jadhav.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="108">
<key>jain-mobicom05</key>
<inproceedings>
<author>
<person>Ravi Jain</person>
<person>Dan Lelescu</person>
<person>Mahadevan Balakrishnan</person>
</author>
<title>Model T: an empirical model for user registration patterns in a campus wireless LAN</title>
<booktitle>Proceedings of the Eleventh Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<pages>170-184</pages>
<month>--08--</month>
<year>2005</year>
<address>Cologne, Germany</address>
<url>http://doi.acm.org/10.1145/1080829.1080848</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="109">
<key>jamieson-realworld</key>
<inproceedings>
<author>
<person>Kyle Jamieson</person>
<person>Bret Hull</person>
<person>Allen Miu</person>
<person>Hari Balakrishnan</person>
</author>
<title>Understanding the Real-World Performance of Carrier Sense</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-JamHul.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="110">
<key>jardosh-association</key>
<inproceedings>
<author>
<person>Amit P. Jardosh</person>
<person>Kimaya Mittal</person>
<person>Krishna Ramachandran</person>
<person>Elizabeth M. Belding</person>
<person>Kevin C. Almeroth</person>
</author>
<title>IQU: Practical Queue-Based User Association Management for WLANs</title>
<booktitle>Proceedings of the Twelfth Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<month>--09--</month>
<year>2006</year>
<address>Los Angeles, CA</address>
<url>http://www.cs.ucsb.edu/~ebelding/txt/mobicom06.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ucsb_ietf2005</keywords>
<keywords>crawdad</keywords>
<refnames><refname>ucsb/ietf2005</refname>
</refnames>
</inproceedings>
<pubdate>20060901</pubdate>
</paper>

<paper id="111">
<key>jardosh-congestion</key>
<inproceedings>
<author>
<person>Amit P. Jardosh</person>
<person>Krishna N. Ramachandran</person>
<person>Kevin C. Almeroth</person>
<person>Elizabeth M. Belding-Royer</person>
</author>
<title>Understanding Congestion in IEEE 802.11b Wireless Networks</title>
<booktitle>Proceedings of the Internet Measurement Conference</booktitle>
<month>--10--</month>
<year>2005</year>
<address>Berkeley, CA</address>
<url>http://moment.cs.ucsb.edu/conan/jardosh-imc2005.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ucsb_ietf2005</keywords>
<keywords>crawdad</keywords>
<refnames><refname>ucsb/ietf2005</refname>
</refnames>
</inproceedings>
<pubdate>20051001</pubdate>
</paper>

<paper id="112">
<key>jardosh-link-layer</key>
<inproceedings>
<author>
<person>Amit P. Jardosh</person>
<person>Krishna N. Ramachandran</person>
<person>Kevin C. Almeroth</person>
<person>Elizabeth M. Belding-Royer</person>
</author>
<title>Understanding Link-layer Behavior in Congested IEEE 802.11b Wireless Networks</title>
<booktitle>Proceedings of the ACM SIGCOMM Workshop on Experimental Approaches to Wireless Network Design and Analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-JarRam.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ucsb_ietf2005</keywords>
<keywords>crawdad</keywords>
<refnames><refname>ucsb/ietf2005</refname>
</refnames>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="113">
<key>jetcheva-metropolitan</key>
<inproceedings>
<author>
<person>Jetcheva, J.G.</person>
<person>Hu, Y.-C.</person>
<person>PalChaudhuri, S.</person>
<person>Saha, A.K.</person>
<person>Johnson, D.B.</person>
</author>
<title>Design and evaluation of a metropolitan area multitier wireless ad hoc network architecture</title>
<booktitle>Proceedings of the 5th IEEE Workshop on Mobile Computing Systems and Applications</booktitle>
<month>--10--</month>
<year>2003</year>
<pages>32-43</pages>
<url>http://doi.ieeecomputersociety.org/10.1109/MCSA.2003.1240765</url>
<address>Monterey, CA, USA</address>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>rice_ad_hoc_city</keywords>
<keywords>crawdad</keywords>
<refnames><refname>rice/ad_hoc_city</refname>
</refnames>
</inproceedings>
<pubdate>20031001</pubdate>
</paper>

<paper id="114">
<key>jiang-correction</key>
<inproceedings>
<author><person>Wenyu Jiang</person>
</author>
<title>Bit Error Correction Without Redundant Data: A MAC Layer Technique for 802.11 Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/03-02.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="115">
<key>jones-practical</key>
<inproceedings>
<author>
<person>Evan P.C. Jones</person>
<person>Lily Li</person>
<person>Paul A.S. Ward</person>
</author>
<title>Practical Routing in Delay-Tolerant Networks</title>
<booktitle>Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking</booktitle>
<month>--08--</month>
<year>2005</year>
<pages>237-243</pages>
<address>Philadelphia, PA, USA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-JonLi.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="116">
<key>judd-replaying</key>
<inproceedings>
<author>
<person>Glenn Judd</person>
<person>Peter Steenkiste</person>
</author>
<title>A Simple Mechanism for Capturing and Replaying Wireless Channels</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-JudSte.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="117">
<key>jung-blueprobe</key>
<inproceedings>
<author>
<person>Sewook Jung</person>
<person>Alexander Chang</person>
<person>Mario Gerla</person>
</author>
<title>Comparison of Bluetooth Interconnection Methods Using BlueProbe</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/03-03.doc</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="118">
<key>kang-extracting</key>
<article>
<author>
<person>Jong Hee Kang</person>
<person>William Welbourne</person>
<person>Benjamin Stewart</person>
<person>Gaetano Borriello</person>
</author>
<title>Extracting places from traces of locations</title>
<journal>SIGMOBILE Mob. Comput. Commun. Rev.</journal>
<volume>9</volume>
<number>3</number>
<year>2005</year>
<url>http://www.cs.washington.edu/homes/jhkang/papers/kang05mc2r.pdf</url>
<issn>1559-1662</issn>
<pages>58-68</pages>
<doi>http://doi.acm.org/10.1145/1094549.1094558</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
<abstract>Location-aware systems are proliferating on a variety of platforms from laptops 
to cell phones. Though these systems offer two principal representations in 
which to work with location (coordinates and landmarks) they do not offer a 
means for working with the userlevel notion of 'place'. A place is a locale 
that is important to a user and which carries a particular semantic meaning 
such as 'my place of work', 'the place we live' or 'my favorite lunch spot'. 
Mobile devices can make more intelligent decisions about how to behave when 
they are equipped with this higher-level information. For example, a cell phone 
can switch to a silent mode when its owner enters a place where a ringer is 
inappropriate (e.g., a movie theater, a lecture hall, a place for personal 
reflection). In this paper, we describe an algorithm for extracting significant 
places from a trace of coordinates. Furthermore, we experimentally evaluate the 
algorithm with real, long-term data collected from three participants using a 
Place Lab client, a software client that computes location coordinates by 
listening for RF-emissions from known radio beacons in the environment (e.g. 
802.11 access points, GSM cell towers). </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>uw_places</keywords>
<keywords>crawdad</keywords>
<refnames><refname>uw/places</refname>
</refnames>
</article>
<pubdate>20050001</pubdate>
</paper>

<paper id="119">
<key>karagiannis-power-law</key>
<inproceedings>
<author>
<person>Thomas Karagiannis</person>
<person>Jean-Yves Le Boudec</person>
<person>Milan Vojnovic</person>
</author>
<title>Power law and exponential decay of inter contact times between mobile devices</title>
<booktitle>MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking</booktitle>
<year>2007</year>
<pages>183-194</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287853.1287875</doi>
<url>http://doi.acm.org/10.1145/1287853.1287875</url>
<publisher>ACM Press</publisher>
<abstract>We examine the fundamental properties that determine the basic performance 
metrics for opportunistic communications. We first consider the distribution of 
inter-contact times between mobile devices. Using a diverse set of measured 
mobility traces, we find as an invariant property that there is a 
characteristic time, order of half a day, beyond which the distribution decays 
exponentially. Up to this value, the distribution in many cases follows a power 
law, as shown in recent work. This power law finding was previously used to 
support the hypothesis that inter-contact time has a power law tail, and that 
common mobility models are not adequate. However, we observe that the time 
scale of interest for opportunistic forwarding may be of the same order as the 
characteristic time, and thus the exponential tail is important. We further 
show that already simple models such as random walk and random waypoint can 
exhibit the same dichotomy in the distribution of inter-contact time asc in 
empirical traces. Finally, we perform an extensive analysis of several 
properties of human mobility patterns across several dimensions, and we present 
empirical evidence that the return time of a mobile device to its favorite 
location site may already explain the observed dichotomy. Our findings suggest 
that existing results on the performance of forwarding schemes based on 
power-law tails might be overly pessimistic. </abstract>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="120">
<key>karande-channel-state</key>
<inproceedings>
<author>
<person>Shirish Karande</person>
<person>Syed Ali Khayam</person>
<person>Yongju Cho</person>
<person>Kiran Misra</person>
<person>Hayder Radha</person>
<person>Jae-Gon Kim</person>
<person>Jin-Woo Hong</person>
</author>
<title>On Channel State Inference and Prediction using Observable Variables in 802.11b Networks</title>
<keywords>crawdad</keywords>
<keywords>niit_bit_errors</keywords>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the IEEE International Conference on Communications (ICC)</booktitle>
<pages>4554-4559</pages>
<month>--06--</month>
<year>2007</year>
<address>New York</address>
<publisher>IEEE Computer Society Press</publisher>
<url>http://ieeexplore.ieee.org/iel5/4288670/4288671/04289423.pdf</url>
<refnames><refname>niit/bit_errors</refname>
</refnames>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="121">
<key>kaul-topologies</key>
<inproceedings>
<author>
<person>Sanjit Krishnan Kaul</person>
<person>Marco Gruteser</person>
<person>Ivan Seskar</person>
</author>
<title>Creating wireless multi-hop topologies on space-constrained indoor testbeds through noise injection</title>
<booktitle>Proceedings of the 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (TRIDENTCOM 2006)</booktitle>
<month>--03--</month>
<year>2006</year>
<doi>http://doi.acm.org/10.1145/1132983.1132986</doi>
<url>http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1649191</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>rutgers_noise</keywords>
<keywords>crawdad</keywords>
<refnames><refname>rutgers/noise</refname>
</refnames>
<abstract>To evaluate routing protocols on a controlled indoor wireless testbed, the 
radio range must be compressed so that larger multi-hop topologies can be 
mapped into a laboratory-size area. We propose noise injection as a more 
flexible option than hardware attenuation and consider methods for mapping real 
world wireless network topologies onto the testbed. Our experimental results 
show that additive white Gaussian noise effectively reduces the radio range, 
without the need for hardware attenuation and careful shielding of wireless 
cards. We performed experiments for a free space propagation environment. By 
selecting node positions through an automated procedure, we were able to create 
a 5-node/4-hop string topology and a random partially connected 6-node topology 
in a 8m by 8m area with off-the-shelf IEEE 802.11 hardware. </abstract>
</inproceedings>
<pubdate>20060301</pubdate>
</paper>

<paper id="122">
<key>kawadia-experimental</key>
<inproceedings>
<author>
<person>Vikas Kawadia</person>
<person>P. R. Kumar</person>
</author>
<title>Experimental Investigations into TCP Performance over Wireless Multihop Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-KawKum.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="123">
<key>kazemi-mman</key>
<inproceedings>
<author>
<person>H. Kazemi</person>
<person>G. C. Hadjichristofi</person>
<person>LDaSilva</person>
</author>
<title>MMAN - A Monitor for Mobile Ad Hoc Networks: Design, Implementation and Experimental Evaluation</title>
<year>2008</year>
<booktitle>Proceedings of the Third ACM International Workshop on Wireless Network Testbeds, Experimental evaluation and CHaracterization (WiNTECH)</booktitle>
<address>San Francisco, CA</address>
<month>--09--</month>
<url>http://www.maniacchallenge.org/kazemi.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>vt_maniac</keywords>
<keywords>crawdad</keywords>
<refnames><refname>vt/maniac</refname>
</refnames>
<abstract>Mobile Ad hoc NETworks (MANETs) are networks in which mobile routers are 
connected via wireless links forming dynamic topologies. An important function 
of network management in a MANET is to observe network conditions: at the node 
level, this may mean keeping track of the traffic load; at the network level, 
the system must monitor active routes and changes in the network topology. In 
this research, we introduce a Monitor for Mobile Ad hoc Networks, (MMAN) to 
address the challenges of monitoring MANETs. We formulate an overall design 
structure and present an implementation of our framework for a MANET running 
the Optimized Link State Routing (OLSR) protocol. The unobtrusive and 
distributed nature of MMAN allows the system to adapt to the constantly 
changing nature of MANETs and to provide valuable network management, security 
assessment, and traffic analysis information. Our system produces a dynamic 
picture of the network level and node level information on a graphical user 
interface. The system is non-intrusive, generates no additional traffic on the 
MANET it monitors, and requires only modest processing and storage resources. </abstract>
</inproceedings>
<pubdate>20080901</pubdate>
</paper>

<paper id="124">
<key>kiess-exc</key>
<inproceedings>
<author>
<person>Wolfgang Kiess</person>
<person>Thomas Ogilvie</person>
<person>Martin Mauve</person>
</author>
<title>The EXC Toolkit for Real-World Experiments with Wireless Multihop Networks</title>
<month>--06--</month>
<year>2008</year>
<booktitle>EXPONWIRELESS 2008: Proceeding of the 3rd Workshop on Advanced Experimental Activities on Wireless Networks and Systems</booktitle>
<address>Newport Beach, California, USA</address>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_collect_multihop_EXC</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/collect/multihop/EXC</refname>
</refnames>
</inproceedings>
<pubdate>20080601</pubdate>
</paper>

<paper id="125">
<key>kim-classify</key>
<inproceedings>
<author>
<person>Minkyong Kim</person>
<person>David Kotz</person>
</author>
<title>Classifying the Mobility of Users and the Popularity of Access Points</title>
<booktitle>Proceedings of the International Workshop on Location- and Context-Awareness (LoCA)</booktitle>
<editor>Thomas Strang and Claudia Linnhoff-Popien</editor>
<month>--05--</month>
<year>2005</year>
<series>Lecture Notes in Computer Science</series>
<volume>3479</volume>
<pages>198-209</pages>
<publisher>Springer-Verlag</publisher>
<copyright>Springer-Verlag</copyright>
<address>Germany</address>
<url>http://www.cs.dartmouth.edu/~dfk/papers/kim:classify.pdf</url>
<category>mobile, crawdad</category>
<keyword>wireless network, location aware, localization, location prediction, location tracking, mobile computing</keyword>
<abstract>There is increasing interest in location-aware systems and applications. It is 
important for any designer of such systems and applications to understand the 
nature of user and device mobility. Furthermore, an understanding of the effect 
of user mobility on access points (APs) is also important for designing, 
deploying, and managing wireless networks. Although various studies of wireless 
networks have provided insights into different network environments and user 
groups, it is often hard to apply these findings to other situations, or to 
derive useful abstract models. \par In this paper, we present a general 
methodology for extracting mobility information from wireless network traces, 
and for classifying mobile users and APs. We used the Fourier transform to 
convert time-dependent location information to the frequency domain, then chose 
the two strongest periods and used them as parameters to a classification 
system based on Bayesian theory. To classify mobile users, we computed diameter 
(the maximum distance between any two APs visited by a user during a fixed time 
period) and observed how this quantity changes or repeats over time. We found 
that user mobility had a strong period of one day, but there was also a large 
group of users that had either a much smaller or much bigger primary period. 
Both primary and secondary periods had important roles in determining classes 
of mobile users. Users with one day as their primary period and a smaller 
secondary period were most prevalent; we expect that they were mostly students 
taking regular classes. To classify APs, we counted the number of users visited 
each AP. The primary period did not play a critical role because it was equal 
to one day for most of the APs; the secondary period was the determining 
parameter. APs with one day as their primary period and one week as their 
secondary period were most prevalent. By plotting the classes of APs on our 
campus map, we discovered that this periodic behavior of APs seemed to be 
independent of their geographical locations, but may depend on the relative 
locations of nearby APs. Ultimately, we hope that our study can help the design 
of location-aware services by providing a base for user mobility models that 
reflect the movements of real users. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20050501</pubdate>
</paper>

<paper id="126">
<key>kim-classify-tr</key>
<techreport>
<author>
<person>Minkyong Kim</person>
<person>David Kotz</person>
</author>
<title>Classifying the Mobility of Users and the Popularity of Access Points</title>
<year>2005</year>
<month>--05--</month>
<number>TR2005-540</number>
<institution>Dept. of Computer Science, Dartmouth College</institution>
<copyright>the authors</copyright>
<category>mobile, crawdad</category>
<url>http://www.cs.dartmouth.edu/reports/abstracts/TR2005-540/</url>
<keyword>wireless network, location aware, localization, location prediction, location tracking, mobile computing</keyword>
<abstract>There is increasing interest in location-aware systems and applications. It is 
important for any designer of such systems and applications to understand the 
nature of user and device mobility. Furthermore, an understanding of the effect 
of user mobility on access points (APs) is also important for designing, 
deploying, and managing wireless networks. Although various studies of wireless 
networks have provided insights into different network environments and user 
groups, it is often hard to apply these findings to other situations, or to 
derive useful abstract models.\par In this paper, we present a general 
methodology for extracting mobility information from wireless network traces, 
and for classifying mobile users and APs. We used the Fourier transform to 
convert time-dependent location information to the frequency domain, then chose 
the two strongest periods and used them as parameters to a classification 
system based on Bayesian theory. To classify mobile users, we computed diameter 
(the maximum distance between any two APs visited by a user during a fixed time 
period) and observed how this quantity changes or repeats over time. We found 
that user mobility had a strong period of one day, but there was also a large 
group of users that had either a much smaller or much bigger primary period. 
Both primary and secondary periods had important roles in determining classes 
of mobile users. Users with one day as their primary period and a smaller 
secondary period were most prevalent; we expect that they were mostly students 
taking regular classes. To classify APs, we counted the number of users visited 
each AP. The primary period did not play a critical role because it was equal 
to one day for most of the APs; the secondary period was the determining 
parameter. APs with one day as their primary period and one week as their 
secondary period were most prevalent. By plotting the classes of APs on our 
campus map, we discovered that this periodic behavior of APs seemed to be 
independent of their geographical locations, but may depend on the relative 
locations of nearby APs. Ultimately, we hope that our study can help the design 
of location-aware services by providing a base for user mobility models that 
reflect the movements of real users. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</techreport>
<pubdate>20050501</pubdate>
</paper>

<paper id="127">
<key>kim-jclassify</key>
<article>
<author>
<person>Minkyong Kim</person>
<person>David Kotz</person>
</author>
<title>Periodic properties of user mobility and access-point popularity</title>
<journal>Journal of Personal and Ubiquitous Computing</journal>
<year>2006</year>
<url>http://dx.doi.org/10.1007/s00779-006-0093-4</url>
<category>wireless, crawdad</category>
<keyword>Wireless network, user mobility, popularity of access points, periodicity</keyword>
<abstract>Understanding user mobility and its effect on access points (APs) is important 
in designing location-aware systems and wireless networks. Although various 
studies of wireless networks have provided useful insights, it is hard to apply 
them to other situations. Here we present a general methodology for extracting 
mobility information from wireless network traces, and for classifying mobile 
users and APs. We used the Fourier transform to reveal important periods and 
chose the two strongest to serve as parameters to a classification system based 
on Bayes' theory. Analysis of one-month traces shows that while a daily pattern 
is common among both users and APs, a weekly pattern is common only for APs. 
Analysis of one-year traces revealed that both user mobility and AP popularity 
depend on the academic calendar. By plotting the classes of APs on our campus 
map, we discovered that their periodic behavior depends on their proximity to 
other APs. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</article>
<pubdate>20060001</pubdate>
</paper>

<paper id="128">
<key>kim-measurement</key>
<inproceedings>
<author>
<person>Seungbae Kim</person>
<person>Xiaofei Wang</person>
<person>Hyunchul Kim</person>
<person>Ted Kwon</person>
<person>Yanghee Choi</person>
</author>
<title>Measurement and Analysis of BitTorrent Traffic in Mobile WiMAX</title>
<booktitle>Proceedings of the 2010 IEEE Tenth International Conference on Peer-to-Peer Computing (P2P)</booktitle>
<pages>1-4</pages>
<year>2010</year>
<address>Delft, Netherlands</address>
<month>--08--</month>
<publisher>IEEE</publisher>
<url>http://mmlab.snu.ac.kr/~sbkim/paper/IEEE_P2P_2010.pdf</url>
<abstract>As mobile Internet environments are becoming dominant, how to revamp P2P 
operations for mobile hosts is gaining more and more attention. In this paper, 
we carry out empirical traffic measurement of BitTorrent service in various 
settings (static, bus and subway) in commercial WiMAX networks. To this end, we 
analyze the connectivity among peers, the download throughput/stability, and 
the signaling overhead of mobile WiMAX hosts in comparison to a wired 
(Ethernet) host. We find out the drawbacks of BitTorrent operations in mobile 
Internet are characterized by lower connection ratio, unstable connections 
amongst peers, and higher control message overhead. </abstract>
<doi>10.1109/P2P.2010.5569997</doi>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>snu_bittorrent</keywords>
<keywords>crawdad</keywords>
<category>wireless-meas,crawdad</category>
<refnames><refname>snu/bittorrent</refname>
</refnames>
</inproceedings>
<pubdate>20100801</pubdate>
</paper>

<paper id="129">
<key>kim-mobility</key>
<inproceedings>
<author>
<person>Minkyong Kim</person>
<person>David Kotz</person>
<person>Songkuk Kim</person>
</author>
<title>Extracting a mobility model from real user traces</title>
<booktitle>Proceedings of the 25th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<year>2006</year>
<month>--04--</month>
<address>Barcelona, Spain</address>
<category>mobile,crawdad</category>
<url>http://www.cs.dartmouth.edu/~dfk/papers/kim:mobility.pdf</url>
<keyword>mobile computing, wireless network</keyword>
<abstract>Understanding user mobility is critical for simulations of mobile devices in a 
wireless network, but current mobility models often do not reflect real user 
movements. In this paper, we provide a foundation for such work by exploring 
mobility characteristics in traces of mobile users. We present a method to 
estimate the physical location of users from a large trace of mobile devices 
associating with access points in a wireless network. Using this method, we 
extracted tracks of always-on Wi-Fi devices from a 13-month trace. We 
discovered that the speed and pause time each follow a log-normal distribution 
and that the direction of movements closely reflects the direction of roads and 
walkways. Based on the extracted mobility characteristics, we developed a 
mobility model, focusing on movements among popular regions. Our validation 
shows that synthetic tracks match real tracks with a median relative error of 
17\%. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="130">
<key>kim-modeling</key>
<inproceedings>
<author>
<person>Minkyong Kim</person>
<person>David Kotz</person>
</author>
<title>Modeling Users' Mobility among WiFi Access Points</title>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>19-24</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://www.cs.dartmouth.edu/~dfk/papers/kim:hotspots.pdf</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="131">
<key>kim-wardriving</key>
<inproceedings>
<author>
<person>Minkyong Kim</person>
<person>Jeff Fielding</person>
<person>David Kotz</person>
</author>
<title>Risks of using AP locations discovered through war driving</title>
<booktitle>Proceedings of the Fourth International Conference on Pervasive Computing</booktitle>
<year>2006</year>
<month>--05--</month>
<category>mobile</category>
<url>http://www.cs.dartmouth.edu/~minkyong/papers/minkyong-pervasive06-v20060503.pdf</url>
<keyword>mobile computing, pervasive computing, context-aware computing, wardriving, wireless networks, mobility modeling</keyword>
<abstract>Many pervasive-computing applications depend on knowledge of user location. 
Because most current location-sensing techniques work only either indoors or 
outdoors, researchers have started using 802.11 beacon frames from access 
points (APs) to provide broader coverage. To use 802.11 beacons, they need to 
know AP locations. Because the actual locations are often unavailable, they use 
estimated locations from \emphwar driving. But these estimated locations may be 
different from actual locations. In this paper, we analyzed the errors in these 
estimates and the effect of these errors on other applications that depend on 
them. We found that the estimated AP locations have a median error of 
35 meters. We considered the error in tracking user positions both indoors and 
outdoors. Using actual AP locations, we could improve the accuracy as much as 
72\% for indoors and 42\% for outdoors. We also analyzed the effect of using 
estimated AP locations in computing AP coverage range and estimating 
interference among APs. The coverage range appeared to be shorter and the 
interference appeared to be more severe than in reality. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_wardriving</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/wardriving</refname>
</refnames>
</inproceedings>
<pubdate>20060501</pubdate>
</paper>

<paper id="132">
<key>king-802-11</key>
<inproceedings>
<author>
<person>Thomas King</person>
<person>Thomas Haenselmann</person>
<person>Wolfgang Effelsberg</person>
</author>
<title>Deployment, Calibration, and Measurement Factors for Position Errors in 802.11-based Indoor Positioning Systems</title>
<booktitle>Proceedings of the International Workshop on Location- and Context-Awareness (LoCA)</booktitle>
<editor>Jeffrey Hightower and Bernt Schiele and Thomas Strang</editor>
<address>Germany</address>
<month>--09--</month>
<year>2007</year>
<series>Lecture Notes in Computer Science</series>
<volume>4718</volume>
<pages>17-34</pages>
<publisher>Springer-Verlag</publisher>
<copyright>Springer-Verlag</copyright>
<url>http://www.informatik.uni-mannheim.de/pi4/publications/King2007i.pdf</url>
<category>mobile, crawdad</category>
<abstract>Indoor positioning systems based on 802.11 and fingerprints offer reasonably 
low position errors. We study the deployment, calibration, and measurement 
factors for position errors by systematically investigating (1) the number of 
access points, (2) the number of samples in the training phase, (3) the number 
of samples in the position determination phase, and (4) the setup of the grid 
of reference points. Further, we bring out the best of the positioning system 
by selecting advantageous values for these parameters. For our study, we 
utilize a test environment with a size of about 312 square meters that is 
covered with 612 reference points arranged in an equally spaced grid. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mannheim_compass</keywords>
<keywords>crawdad</keywords>
<refnames><refname>mannheim/compass</refname>
</refnames>
</inproceedings>
<pubdate>20070901</pubdate>
</paper>

<paper id="133">
<key>king-compass</key>
<inproceedings>
<author>
<person>T. King</person>
<person>S. Kopf</person>
<person>T. Haenselmann</person>
<person>C. Lubberger</person>
<person>W. Effelsberg</person>
</author>
<title>COMPASS: A Probabilistic Indoor Positioning System Based on 802.11 and Digital Compasses</title>
<booktitle>Proceedings of the First ACM International Workshop on Wireless Network Testbeds, Experimental evaluation and CHaracterization (WiNTECH)</booktitle>
<month>--09--</month>
<year>2006</year>
<address>Los Angeles, CA, USA</address>
<url>http://www.informatik.uni-mannheim.de/pi4/publications/King2006g.pdf</url>
<abstract>Positioning systems are one of the key elements required by location-based 
services. This paper presents the design, implementation and analysis of a 
positioning system called COMPASS which is based on 802.11-compliant network 
infrastructure and digital compasses. On the mobile device, COMPASS samples the 
signal strength values of different access points in its communication range 
and utilizes the orientation of the user to preselect a subset of the training 
data. The remaining training data is used by a probabilistic positioning 
algorithm to determine the position of the user. While prior systems show 
limited accuracy due to blocking effects caused by the human body, we apply 
digital compasses to detect the orientations of the users so that we can deal 
with these blocking effects. After a short period of training our COMPASS 
system achieves an average error distance of less than 1.65 meters in our 
experimental environment of 312 square meters. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mannheim_compass</keywords>
<keywords>crawdad</keywords>
<refnames><refname>mannheim/compass</refname>
</refnames>
</inproceedings>
<pubdate>20060901</pubdate>
</paper>

<paper id="134">
<key>king-fingerprint</key>
<inproceedings>
<author>
<person>Thomas King</person>
<person>Thomas Haenselmann</person>
<person>Wolfgang Effelsberg</person>
</author>
<title>On-Demand Fingerprint Selection for 802.11-based Positioning Systems</title>
<booktitle>Proceedings of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM)</booktitle>
<month>--06--</month>
<year>2008</year>
<address>Newport Beach, CA</address>
<url>http://www.informatik.uni-mannheim.de/pi4/publications/King2008b.pdf</url>
<abstract>Fingerprinting is a popular technology for 802.11-based positioning systems: 
Radio characteristics from different access points are measured at various 
positions and stored in a database. The database is copied to all mobile 
devices, and in case that a position estimate is needed, the device compares 
its currently measured radio characteristics with all the database entries. In 
this paper, we present two on-demand fingerprint selection algorithms to avoid 
the cumbersome and time-consuming approach of manually copying all 
fingerprints. Our algorithms only request those fingerprints from the database 
that are currently required to compute a position. The two algorithms differ in 
the way they shape the region for which fingerprints are requested. On-demand 
selection also allows storage-restricted mobile devices to utilize the 
positioning system. We carefully evaluate our algorithms in a real-world 
experiment. The results show that our algorithms do not harm the position 
accuracy of the positioning system. In addition, we analyze the space 
requirements of our algorithms and show that the typical constraints of mobile 
devices are met. </abstract>
<category>mobile, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mannheim_compass</keywords>
<keywords>crawdad</keywords>
<refnames><refname>mannheim/compass</refname>
</refnames>
</inproceedings>
<pubdate>20080601</pubdate>
</paper>

<paper id="135">
<key>king-tools</key>
<inproceedings>
<author>
<person>Thomas King</person>
<person>Thomas Butter</person>
<person>Hendrik Lemelson</person>
<person>Thomas Haenselmann</person>
<person>Wolfgang Effelsberg</person>
</author>
<title>Loc(lib,trace,eva,ana): Research Tools for 802.11-based Positioning Systems</title>
<year>2007</year>
<pages>67-74</pages>
<booktitle>Proceedings of the Second ACM International Workshop on Wireless Network Testbeds, Experimental evaluation and CHaracterization (WiNTECH)</booktitle>
<address>Montreal, QC, Canada</address>
<month>--09--</month>
<url>http://www.informatik.uni-mannheim.de/pi4/publications/King2007f.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_collect_location_loclib</keywords>
<keywords>tools_collect_location_loctrace</keywords>
<keywords>tools_analyze_location_locana</keywords>
<keywords>tools_analyze_location_loceva</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/collect/location/loclib</refname>
<refname>tools/collect/location/loctrace</refname>
<refname>tools/analyze/location/locana</refname>
<refname>tools/analyze/location/loceva</refname>
</refnames>
<abstract>802.11-based positioning systems are a hot topic in research. However, no 
standardized set of tools has been established to facilitate the research 
process. In this paper, we contribute our research tools to the community. The 
benefit for the community is considerable: (1) Standardized tools reduce the 
amount of work each researcher has to spend to build software to collect signal 
strength samples and process this data. (2) The confidence in the correctness 
of the tools increases because everybody is encouraged to submit bugfixes. (3) 
A unified evaluation process makes results mutually comparable. (4) We hope 
other researchers contribute to our tools. </abstract>
</inproceedings>
<pubdate>20070901</pubdate>
</paper>

<paper id="136">
<key>klasnja-wifi-privacy</key>
<inproceedings>
<author>
<person>Klasnja, Predrag</person>
<person>Consolvo, Sunny</person>
<person>Jung, Jaeyeon</person>
<person>Greenstein, Benjamin M.</person>
<person>LeGrand, Louis</person>
<person>Powledge, Pauline</person>
<person>Wetherall, David</person>
</author>
<title>When I am on Wi-Fi, I am fearless": privacy concerns &amp; practices in eeryday Wi-Fi use</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_process_pcap_Wifipcap</keywords>
<keywords>crawdad</keywords>
<booktitle>CHI '09: Proceedings of the 27th international conference on Human factors in computing systems</booktitle>
<year>2009</year>
<isbn>978-1-60558-246-7</isbn>
<pages>1993-2002</pages>
<location>Boston, MA, USA</location>
<doi>http://doi.acm.org/10.1145/1518701.1519004</doi>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<category>wireless-meas,crawdad</category>
<refnames><refname>tools/process/pcap/Wifipcap</refname>
</refnames>
</inproceedings>
<pubdate>20090001</pubdate>
</paper>

<paper id="137">
<key>kompella-scheduling</key>
<inproceedings>
<author>
<person>Ramana Rao Kompella</person>
<person>Narayanan Ramabhadran</person>
<person>Ishwar Ramani</person>
<person>Alex Snoeren</person>
</author>
<title>Cooperative Scheduling Via Pipelining in 802.11 Wireless Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-KomRam.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="138">
<key>kotz-axioms</key>
<inproceedings>
<author>
<person>David Kotz</person>
<person>Calvin Newport</person>
<person>Robert S. Gray</person>
<person>Jason Liu</person>
<person>Yougu Yuan</person>
<person>Chip Elliott</person>
</author>
<title>Experimental Evaluation of Wireless Simulation Assumptions</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)</booktitle>
<year>2004</year>
<month>--10--</month>
<pages>78-82</pages>
<publisher>ACM Press</publisher>
<copyright>ACM</copyright>
<url>http://www.cs.dartmouth.edu/~dfk/papers/kotz:axioms.pdf</url>
<keyword>wireless network, mobile computing, ad hoc network, dfk, MANET</keyword>
<abstract>All analytical and simulation research on ad hoc wireless networks must 
necessarily model radio propagation using simplifying assumptions. We provide a 
comprehensive review of six assumptions that are still part of many ad hoc 
network simulation studies, despite increasing awareness of the need to 
represent more realistic features, including hills, obstacles, link 
asymmetries, and unpredictable fading. We use an extensive set of measurements 
from a large outdoor routing experiment to demonstrate the weakness of these 
assumptions, and show how these assumptions cause simulation results to differ 
significantly from experimental results. We close with a series of 
recommendations for researchers, whether they develop protocols, analytic 
models, or simulators for ad hoc wireless networks. </abstract>
</inproceedings>
<pubdate>20041001</pubdate>
</paper>

<paper id="139">
<key>kotz-campus</key>
<inproceedings>
<author>
<person>David Kotz</person>
<person>Kobby Essien</person>
</author>
<title>Analysis of a Campus-wide Wireless Network</title>
<booktitle>Proceedings of the Eighth Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<pages>107-118</pages>
<month>--09--</month>
<year>2002</year>
<note>Revised and corrected as Dartmouth CS Technical Report TR2002-432</note>
<url>http://www.cs.dartmouth.edu/~dfk/papers/kotz:campus.pdf</url>
<keyword>mobile computing, wireless network, workload characterization, Dartmouth, dfk</keyword>
<abstract>Understanding usage patterns in wireless local-area networks (WLANs) is 
critical for those who develop, deploy, and manage WLAN technology, as well as 
those who develop systems and application software for wireless networks. This 
paper presents results from the largest and most comprehensive trace of network 
activity in a large, production wireless LAN. For eleven weeks we traced the 
activity of nearly two thousand users drawn from a general campus population, 
using a campus-wide network of 476 access points spread over 161 buildings. Our 
study expands on those done by Tang and Baker, with a significantly larger and 
broader population. \par We found that residential traffic dominated all other 
traffic, particularly in residences populated by newer students; students are 
increasingly choosing a wireless laptop as their primary computer. Although web 
protocols were the single largest component of traffic volume, network backup 
and file sharing contributed an unexpectedly large amount to the traffic. 
Although there was some roaming within a network session, we were surprised by 
the number of situations in which cards roamed excessively, unable to settle on 
one access point. Cross-subnet roams were an especial problem, because they 
broke IP connections, indicating the need for solutions that avoid or 
accommodate such roams. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/campus</refname>
</refnames>
</inproceedings>
<pubdate>20020901</pubdate>
</paper>

<paper id="140">
<key>kotz-crawdad</key>
<article>
<author>
<person>David Kotz</person>
<person>Tristan Henderson</person>
</author>
<title>CRAWDAD: A Community Resource for Archiving Wireless Data at Dartmouth</title>
<journal>IEEE Pervasive Computing</journal>
<pages>12-14</pages>
<month>--10--</month>
<year>2005</year>
<volume>4</volume>
<number>4</number>
<url>http://ieeexplore.ieee.org/iel5/7756/32928/01541962.pdf?tp=&amp;arnumber=1541962&amp;isnumber=32928</url>
<category>crawdad</category>
</article>
<pubdate>20051001</pubdate>
</paper>

<paper id="141">
<key>kotz-jcampus</key>
<article>
<author>
<person>David Kotz</person>
<person>Kobby Essien</person>
</author>
<title>Analysis of a Campus-wide Wireless Network</title>
<journal>Wireless Networks</journal>
<pages>115-133</pages>
<year>2005</year>
<volume>11</volume>
<copyright>Springer Science and Business Media</copyright>
<url>http://www.cs.dartmouth.edu/~dfk/papers/kotz:jcampus.pdf</url>
<keyword>mobile computing, wireless network, workload characterization, Dartmouth, dfk</keyword>
<abstract>Understanding usage patterns in wireless local-area networks (WLANs) is 
critical for those who develop, deploy, and manage WLAN technology, as well as 
those who develop systems and application software for wireless networks. This 
paper presents results from the largest and most comprehensive trace of network 
activity in a large, production wireless LAN. For eleven weeks we traced the 
activity of nearly two thousand users drawn from a general campus population, 
using a campus-wide network of 476 access points spread over 161 buildings at 
Dartmouth College. Our study expands on those done by Tang and Baker, with a 
significantly larger and broader population. \par We found that residential 
traffic dominated all other traffic, particularly in residences populated by 
newer students; students are increasingly choosing a wireless laptop as their 
primary computer. Although web protocols were the single largest component of 
traffic volume, network backup and file sharing contributed an unexpectedly 
large amount to the traffic. Although there was some roaming within a network 
session, we were surprised by the number of situations in which cards roamed 
excessively, unable to settle on one access point. Cross-subnet roams were an 
especial problem, because they broke IP connections, indicating the need for 
solutions that avoid or accommodate such roams. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/campus</refname>
</refnames>
</article>
<pubdate>20050001</pubdate>
</paper>

<paper id="142">
<key>koukis-anonymization</key>
<inproceedings>
<author>
<person>D. Koukis</person>
<person>S. Antonatos</person>
<person>D. Antoniades</person>
<person>E.P. Markatos</person>
<person>P. Trimintzios</person>
</author>
<title>A Generic Anonymization Framework for Network Traffic</title>
<booktitle>Proceedings of the IEEE International Conference on Communications (ICC)</booktitle>
<month>--06--</month>
<year>2006</year>
<volume>5</volume>
<address>Istanbul, Turkey</address>
<publisher>IEEE Computer Society Press</publisher>
<url>http://www.ics.forth.gr/dcs/Activities/papers/anon.icc06.pdf</url>
<abstract>Lack of trust is one of the main reasons for the limited cooperation between 
different organizations. The privacy of users is of paramount importance to 
administrators and organizations, which are reluctant to cooperate between each 
other and exchange network traffic traces. The main reasons behind reluctance 
to exchange monitored data are the protection of the users's privacy and the 
fear of information leakage about the internal infrastructure. Anonymization is 
the technique to overcome this reluctance and enhance the cooperation between 
different organizations with the smooth exchange of monitored data. Today, 
several organizations provide network traffic traces that are anonymized by 
software utilities or ad-hoc solutions that offer limited flexibility. The 
result of this approach is the creation of unrealistic traces, inappropriate 
for use in evaluation experiments. Furthermore, the need for fast on-line 
anonymization has recently emerged as cooperative defense mechanisms have to 
share network traffic. Our effort focuses on the design and implementation of a 
generic and flexible anonymization framework that provides extended 
functionality, covering multiple aspects of anonymization needs and allowing 
fine-tuning of privacy protection level. The proposed framework is composed by 
an anonymization application programming interface (AAPI). The performance 
results show that AAPI outperforms existing tools, while offering significantly 
more anonymization primitives. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_sanitize_generic_AnonTool</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/sanitize/generic/AnonTool</refname>
</refnames>
</inproceedings>
<pubdate>20060601</pubdate>
</paper>

<paper id="143">
<key>krendzel-load</key>
<inproceedings>
<author>
<person>A. Krendzel</person>
<person>M. PortolÃ©s</person>
<person>J. Mangues</person>
</author>
<title>Methodology for Traffic Load Estimation in WLANs Based on Real Traces</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the 14 European Wireless Conference</booktitle>
<month>--06--</month>
<year>2008</year>
<address>Praga, Czech Republic</address>
<url>http://www.cttc.es/resources/doc/080703-ew-final-web-20332.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20080601</pubdate>
</paper>

<paper id="144">
<key>kumar-gender-poster</key>
<misc>
<author>
<person>Udayan Kumar</person>
<person>Nikhil Yadav</person>
<person>Ahmed Helmy</person>
</author>
<title>Gender-based Feature Analysis in Campus-wide WLANs</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<year>2007</year>
<month>--09--</month>
<category>wireless-meas</category>
<url>http://www.cise.ufl.edu/~ukumar/mobicom_07.pdf</url>
<howpublished>Poster presentation at MobiCom 2007</howpublished>
</misc>
<pubdate>20070901</pubdate>
</paper>

<paper id="145">
<key>kusy-interferometric</key>
<inproceedings>
<author>
<person>Branislav Kusy</person>
<person>Janos Sallai</person>
<person>Gyorgy Balogh</person>
<person>Akos Ledeczi</person>
<person>Vladimir Protopopescu</person>
<person>Johnny Tolliver</person>
<person>Frank DeNap</person>
<person>Morey Parang</person>
</author>
<title>Radio Interferometric Tracking of Mobile Wireless Nodes</title>
<booktitle>Proceedings of the Fifth International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<month>--06--</month>
<year>2007</year>
<url>http://www.isis.vanderbilt.edu/projects/nest/people/brano/pubs/sys5092-kusy.pdf</url>
<address>San Juan, Puerto Rico</address>
<publisher>USENIX Association</publisher>
<keyword>Wireless Sensor Networks, Radio Interferometry, Tracking, Localization, Location-Awareness, Mobility</keyword>
<abstract>Location-awareness is an important requirement for many mobile wireless 
applications today. When GPS is not applicable because of the required 
precision and/or the resource constraints on the hardware platform, radio 
interferometric ranging may offer an alternative. In this paper, we present a 
technique that enables the precise tracking of multiple wireless nodes 
simultaneously. It relies on multiple infrastructure nodes deployed at known 
locations measuring the position of tracked mobile nodes using radio 
interferometry. In addition to location information, the approach also provides 
node velocity estimates by measuring the Doppler shift of the interference 
signal. The performance of the technique is evaluated using a prototype 
implementation on mote-class wireless sensor nodes. Finally, a possible 
application scenario of dirty bomb detection in a football stadium is briefly 
described. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>vanderbilt_interferometric</keywords>
<keywords>crawdad</keywords>
<refnames><refname>vanderbilt/interferometric</refname>
</refnames>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="146">
<key>lacan-multicast</key>
<inproceedings>
<author>
<person>J&#233;r&#244;me Lacan</person>
<person>Tanguy Perennou</person>
</author>
<title>Evaluation of Error Control Mechanisms for 802.11b Multicast Transmissions</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/03-01.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="147">
<key>lamarca-placelab</key>
<inproceedings>
<author>
<person>Anthony LaMarca</person>
<person>Yatin Chawathe</person>
<person>Sunny Consolvo</person>
<person>Jeffrey Hightower</person>
<person>Ian Smith</person>
<person>James Scott</person>
<person>Timothy Sohn</person>
<person>James Howard</person>
<person>Jeff Hughes</person>
<person>Fred Potter</person>
<person>Jason Tabert</person>
<person>Pauline Powledge</person>
<person>Gaetano Borriello</person>
<person>Bill Schilit</person>
</author>
<title>Place Lab: Device Positioning Using Radio Beacons in the Wild</title>
<booktitle>Proceedings of the Third International Conference on Pervasive Computing</booktitle>
<year>2005</year>
<month>--05--</month>
<url>http://www.placelab.org/publications/pubs/pervasive-placelab-2005-final.pdf</url>
<abstract>Location awareness is an important capability for mobile computing. Yet 
inexpensive, pervasive positioning - a requirement for wide-scale adoption of 
location-aware computing - has been elusive. We demonstrate a radio 
beacon-based approach to location, called Place Lab, that can overcome the lack 
of ubiquity and high-cost found in existing location sensing approaches. Using 
Place Lab, commodity laptops, PDAs and cell phones estimate their position by 
listening for the cell IDs of fixed radio beacons, such as wireless access 
points, and referencing the beacons' positions in a cached database. We present 
experimental results showing that 802.11 and GSM beacons are sufficiently 
pervasive in the greater Seattle area to achieve 20-30 meter median accuracy 
with nearly 100% coverage measured by availability in people's daily lives. </abstract>
<category>mobile, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>intel_placelab</keywords>
<keywords>crawdad</keywords>
<refnames><refname>intel/placelab</refname>
</refnames>
</inproceedings>
<pubdate>20050501</pubdate>
</paper>

<paper id="148">
<key>lebrun-content</key>
<inproceedings>
<author>
<person>Jason LeBrun</person>
<person>Chen-Nee Chuah</person>
</author>
<title>Bluetooth content distribution stations on public transit</title>
<booktitle>MobiShare '06: Proceedings of the 1st international workshop on Decentralized resource sharing in mobile computing and networking</booktitle>
<mon>-09-</mon>
<year>2006</year>
<pages>63-65</pages>
<address>Los Angeles, California</address>
<keyword>Bluetooth, DTN, vehicular networ</keyword>
<url>http://doi.acm.org/10.1145/1161252.1161269</url>
<abstract>In this poster, we introduce our Bluespots project, in which a small computer 
on a bus serves as a Bluetooth Content Distribution (BCD) station in a 
university public transit scenario. An important feature of the application 
space that we envision is that it depends only on single hops between devices. 
The primary form of communication will be between user mobile devices and 
Bluespots, or information waypoints. In later incarnations of this system, 
larger-scale dissemination can be achieved by using application-level 
peer-to-peer connections. However, we do not think of the system as a general 
data transit system. We consider it more as an implementation of social 
networking, in which users only participate in functions that are in line with 
their own interests and goals. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ucdavis_unitrans</keywords>
<keywords>crawdad</keywords>
<refnames><refname>ucdavis/unitrans</refname>
</refnames>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="149">
<key>lee-analysis</key>
<inproceedings>
<author>
<person>Jaehwan Lee</person>
<person>Sunghyun Choi</person>
<person>Hanwook Jung</person>
</author>
<title>Analysis of User Behavior and Traffic Pattern in a Large-Scale 802.11a/b Network</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Lee.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="150">
<key>lee-slaw</key>
<inproceedings>
<author>
<person>Kyunghan Lee</person>
<person>Seongik Hong</person>
<person>Seong Joon Kim</person>
<person>Injong Rhee</person>
<person>Song Chong</person>
</author>
<title>SLAW: A Mobility Model for Human Walks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ncsu_mobilitymodels</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the 28th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<month>--04--</month>
<year>2009</year>
<address>Rio de Janeiro, Brazil</address>
<publisher>IEEE</publisher>
<url>http://netsrv.csc.ncsu.edu/export/slaw_infocom_2009.pdf</url>
<category>wireless-meas,crawdad</category>
<refnames><refname>ncsu/mobilitymodels</refname>
</refnames>
</inproceedings>
<pubdate>20090401</pubdate>
</paper>

<paper id="151">
<key>lee-steady-state</key>
<inproceedings>
<author>
<person>Jong-Kwon Lee</person>
<person>Jennifer C. Hou</person>
</author>
<title>Modeling steady-state and transient behaviors of user mobility:: formulation, analysis, and application</title>
<booktitle>MobiHoc '06: Proceedings of the seventh ACM international symposium on Mobile ad hoc networking and computing</booktitle>
<year>2006</year>
<pages>85-96</pages>
<location>Florence, Italy</location>
<url>http://doi.acm.org/10.1145/1132905.1132915</url>
<doi>http://doi.acm.org/10.1145/1132905.1132915</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
<category>wireless-meas, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth/campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="152">
<key>lee-tcp-cdma</key>
<inproceedings>
<author><person>Youngseok Lee</person>
</author>
<title>Measured TCP Performance in CDMA 1x EV-DO Network</title>
<booktitle>PAM 2006, 7th Passive and Active Measurement conference</booktitle>
<year>2006</year>
<month>--03--</month>
<url>http://www.pamconf.org/2006/papers/s1-lee.pdf</url>
<address>Adelaide, Australia</address>
<abstract>This paper investigates the long-lived TCP bulk throughput over the CDMA 1x 
EV-DO service that provides high-speed \always on" Internet connectivity in a 
wide-area mobile environment. Although the peak rates of downlink/uplink are 
speci ed as 2.4 Mbps/153 Kbps, the user-experienced application-layer 
throughput has not been much reported and analyzed. In our experiment, it was 
shown that average TCP throughputs over downlink/uplink are 572.5/94.7Kbps and 
the average packet loss rates of 1x EV-DO downlink/uplink are 0.2/4.7%. The 
average end-to-end round-trip delay was 417.4ms with the variance of 14,995ms. 
Although the packet loss rate is low, bursty packet losses frequently occur 
because of packet corruption with TCP checksum failures, which result in TCP 
performance degradation by the retransmission timeout. Our study showed that 
this TCP checksum errors are related with the TCP/IP header compression 
algorithm at link layer protocols such as PPP. Our measurement-based analysis 
of TCP performance could be used for the correct model of the 3G wireless link 
characteristic and for the real-world simulation of TCP behavior over the 3G 
wireless network. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cnu_cdma</keywords>
<keywords>crawdad</keywords>
<refnames><refname>cnu/cdma</refname>
</refnames>
</inproceedings>
<pubdate>20060301</pubdate>
</paper>

<paper id="153">
<key>leguay-mobility</key>
<inproceedings>
<author>
<person>J&#233;r&#233;mie Leguay</person>
<person>Timur Friedman</person>
<person>Vania Conan</person>
</author>
<title>Evaluating Mobility Pattern Space Routing for DTNs</title>
<booktitle>Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM)</booktitle>
<month>--04--</month>
<year>2006</year>
<address>Barcelona, Spain</address>
<url>http://www-rp.lip6.fr/site_npa/site_rp/_publications/669-infocom06.pdf</url>
<abstract>Because a delay tolerant network (DTN) can often be partitioned, the problem of 
routing is very challenging. However, routing benefits considerably if one can 
take advantage of knowledge concerning node mobility. This paper addresses this 
problem with a generic algorithm based on the use of a high-dimensional 
Euclidean space, that we call MobySpace, constructed upon nodes' mobility 
patterns. We provide here an analysis and the large scale evaluation of this 
routing scheme in the context of ambient networking by replaying real mobil- 
ity traces. The specific MobySpace evaluated is based on the frequency of visit 
of nodes for each possible location. We show that the MobySpace can achieve 
good performance compared to that of the other algorithms we implemented, 
especially when we perform routing on the nodes that have a high connection 
time. We determine that the degree of homogeneity of mobility patterns of nodes 
has a high impact on routing. And finally, we study the ability of nodes to 
learn their own mobility patterns. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="154">
<key>leguay-opportunistic</key>
<inproceedings>
<author>
<person>J&#233;r&#233;mie Leguay</person>
<person>Anders Lindgren</person>
<person>James Scott</person>
<person>Timur Friedman</person>
<person>Jon Crowcroft</person>
</author>
<title>Opportunistic Content Distribution in an Urban Setting</title>
<booktitle>Proceedings of the ACM SIGCOMM Workshop on Challenged Networks (CHANTS 2006)</booktitle>
<address>Pisa, Italy</address>
<month>--09--</month>
<year>2006</year>
<url>http://www-rp.lip6.fr/site_npa/site_rp/_publications/697-chants06.pdf</url>
<abstract>This paper investigates the feasibility of a city-wide content distribution 
architecture composed of short range wireless access points. We look at how a 
target group of intermittently and partially connected mobile nodes can improve 
the diffusion of information within the group by leveraging fixed and mobile 
nodes that are exterior to the group. The fixed nodes are data sources, and the 
external mobile nodes are data relays, and we examine the trade off between the 
use of each in order to obtain high satisfaction within the target group, which 
consists of data sinks. We conducted an experiment in Cambridge, UK, to gather 
mobility traces that we used for the study of this content distribution 
architecture. In this scenario, the simple fact that members of the target 
group collaborate leads to a delivery ratio of 90\%. In addition, the use of 
external mobile nodes to relay the information slightly increases the delivery 
ratio while significantly decreasing the delay. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>upmc_content</keywords>
<keywords>crawdad</keywords>
<refnames><refname>upmc/content</refname>
</refnames>
</inproceedings>
<pubdate>20060901</pubdate>
</paper>

<paper id="155">
<key>li-tools</key>
<inproceedings>
<author>
<person>Feng Li</person>
<person>Mingzhe Li</person>
<person>Rui Lu</person>
<person>Huahui Wu</person>
<person>Mark Claypool</person>
<person>Robert Kinicki</person>
</author>
<title>Tools and Techniques for Measurement of IEEE 802.11 Wireless Networks</title>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/02-01.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_collect_802.11_wrapi_plus</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/collect/802.11/wrapi_plus</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="156">
<key>liu-impala-zebranet</key>
<inproceedings>
<author>
<person>Ting Liu</person>
<person>Christopher Sadler</person>
<person>Pei Zhang</person>
<person>Margaret Martonosi</person>
</author>
<title>Implementing Software on Resource-Constrained Mobile Sensors: Experiences with Impala and ZebraNet</title>
<booktitle>Proceedings of the Second International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<month>--06--</month>
<year>2004</year>
<address>Boston, MA</address>
<publisher>USENIX Association</publisher>
<url>http://portal.acm.org/citation.cfm?id=990064.990095</url>
<keyword>Sensor Networks, Middleware System, Operation Scheduling, Event Handling, Network Communications</keyword>
<abstract>ZebraNet is a mobile, wireless sensor network in which nodes move throughout an 
environment working to gather and process information about their surroundings. 
As in many sensor or wireless systems, nodes have critical resource constraints 
such as processing speed, memory size, and energy supply; they also face 
special hardware issues such as sensing device sample time, data storage/access 
restrictions, and wireless transceiver capabilities. This paper discusses and 
evaluates ZebraNet's system design decisions in the face of a range of 
real-world constraints. Impala-ZebraNet's middleware layer - serves as a 
light-weight operating system, but also has been designed to encourage 
application modularity, simplicity, adaptivity, and repairability. Impala is 
now implemented on ZebraNet hardware nodes, which include a 16-bit 
microcontroller, a low-power GPS unit, a 900MHz radio, and 4Mbits of 
non-volatile FLASH memory. This paper discusses Impala's operation scheduling 
and event handling model, and explains how system constraints and goals led to 
the interface designs we chose between the application, middleware, and 
firmware layers. We also describe Impala's network interface which unifies 
media access control and transport control into an efficient network protocol. 
With the minimum overhead in communication, buffering, and processing, it 
supports a range of message models, all inspired by and tailored to ZebraNet's 
application needs. By discussing design tradeoffs in the context of a real 
hardware system and a real sensor network application, this paper's design 
choices and performance measurements offer some concrete experiences with 
software systems issues for the mobile sensor design space. More generally, we 
feel that these experiences can guide design choices in a range of related 
systems. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>princeton_zebranet</keywords>
<keywords>crawdad</keywords>
<refnames><refname>princeton/zebranet</refname>
</refnames>
</inproceedings>
<pubdate>20040601</pubdate>
</paper>

<paper id="157">
<key>liu-jdirex</key>
<article>
<author>
<person>Jason Liu</person>
<person>Yougu Yuan</person>
<person>David M. Nicol</person>
<person>Robert S. Gray</person>
<person>Calvin C. Newport</person>
<person>David Kotz</person>
<person>Luiz Felipe Perrone</person>
</author>
<title>Empirical Validation of Wireless Models in Simulations of Ad Hoc Routing Protocols</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>Simulation: Transactions of The Society for Modeling and Simulation International</journal>
<volume>81</volume>
<number>4</number>
<year>2005</year>
<month>--04--</month>
<pages>307-323</pages>
<publisher>Sage Publications</publisher>
<copyright>Simulation Councils Inc.</copyright>
<note>``Best of PADS 2004'' special issue</note>
<url>http://www.cs.dartmouth.edu/~dfk/papers/liu:jdirex.pdf</url>
<keyword>wireless network, ad-hoc routing, MANET, simulation</keyword>
<abstract>Computer simulation has been used extensively as an effective tool in the 
design and evaluation of systems. One should not, however, underestimate the 
importance of validation&#x2014; the process of ensuring whether a simulation model 
is an appropriate representation of the real-world system. Validation of 
wireless network simulations is difficult due to strong interdependencies among 
protocols at different layers and uncertainty in the wireless environment. The 
authors present an approach of coupling direct-execution simulation and traces 
from real outdoor experiments to validating simple wireless models that are 
used commonly in simulations of wireless ad hoc networks. This article 
documents a common testbed that supports direct execution of a set of ad hoc 
routing protocol implementations in a wireless network simulator. By comparing 
routing behavior measured in the real experiment with behavior computed by the 
simulation, the authors validate the models of radio behavior upon which 
protocol behavior depends. </abstract>
</article>
<pubdate>20050401</pubdate>
</paper>

<paper id="158">
<key>mahadevan-mobinet</key>
<inproceedings>
<author>
<person>Priya Mahadevan</person>
<person>Adolfo Rodriguez</person>
<person>David Becker</person>
<person>Amin Vahdat</person>
</author>
<title>MobiNet: A Scalable Emulation Infrastructure for Ad hoc and Wireless Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>7-12</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://portal.acm.org/citation.cfm?id=1072432</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="159">
<key>mahajan-vehicles</key>
<inproceedings>
<author>
<person>Ratul Mahajan</person>
<person>John Zahorjan</person>
<person>Brian Zill</person>
</author>
<title>Understanding WiFi-based Connectivity from Moving Vehicles</title>
<booktitle>Proceedings of the Internet Measurement Conference</booktitle>
<month>--10--</month>
<year>2007</year>
<address>San Diego, CA, USA</address>
<url>http://www.imconf.net/imc-2007/papers/imc18.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>microsoft_vanlan</keywords>
<keywords>crawdad</keywords>
<refnames><refname>microsoft/vanlan</refname>
</refnames>
</inproceedings>
<pubdate>20071001</pubdate>
</paper>

<paper id="160">
<key>mahajan-wit</key>
<inproceedings>
<author>
<person>R. Mahajan</person>
<person>M. Rodrig</person>
<person>D. Wetherall</person>
<person>J. Zahorjan</person>
</author>
<title>Analyzing the MAC-level Behavior of Wireless Networks</title>
<booktitle>Proceedings of ACM SIGCOMM 2006</booktitle>
<month>--09--</month>
<year>2006</year>
<address>Pisa, Italy</address>
<url>http://www.cs.washington.edu/research/networking/wireless/bits/sigcomm2006-wit.pdf</url>
<abstract>We present Wit, a non-intrusive tool that builds on passive monitoring to 
analyze the detailed MAC-level behavior of operational wireless networks. Wit 
uses three processing steps to construct an enhanced trace of system activity. 
First, a robust merging procedure combines the necessarily incomplete views 
from multiple, independent monitors into a single, more complete trace of 
wireless activity. Next, a novel inference engine based on formal language 
methods reconstructs packets that were not captured by any monitor and 
determines whether each packet was received by its destination. Finally, Wit 
derives network performance measures from this enhanced trace; we show how to 
estimate the number of stations competing for the medium. We assess Wit with a 
mix of real traces and simulation tests. We find that merging and inference 
both significantly enhance the originally captured trace. We apply Wit to 
multi-monitor traces from a live network to show how it facilitates 802.11 MAC 
analyses that would otherwise be difficult or rely on less accurate heuristics. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_analyze_802.11_Wit</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/analyze/802.11/Wit</refname>
</refnames>
</inproceedings>
<pubdate>20060901</pubdate>
</paper>

<paper id="161">
<key>mahanti-completeness</key>
<inproceedings>
<author>
<person>Aniket Mahanti</person>
<person>Martin Arlitt</person>
<person>Carey Williamson</person>
</author>
<title>Assessing the Completeness of Wireless-side Tracing Mechanisms</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM)</booktitle>
<month>--06--</month>
<year>2007</year>
<address>Helsinki, Finland</address>
<url>http://pages.cpsc.ucalgary.ca/~amahanti/Papers/WoWMoM2007.pdf</url>
<abstract>Analyzing traces of wireless network activity has many pragmatic purposes, from 
capacity planning to network design. Unfortunately, capturing complete traces 
of wireless traffic is difficult, and using incomplete traces can degrade the 
quality of the aforementioned analyses. In this paper we examine three 
different methods for estimating the completeness of wireless traces. We find 
that a method that examines MAC-layer sequence numbers provides the most 
accurate results. We also examine the effect of the placement of wireless 
sensors on the completeness of wirelessside traces. We determine that locating 
sensors such that the signal strengths between clients and access points is 
over 40% results in low miss rates at the sensor, and few CRC errors. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="162">
<key>mahanti-monitoring</key>
<inproceedings>
<author>
<person>Aniket Mahanti</person>
<person>Carey Williamson</person>
<person>Martin Arlitt</person>
<person>Anirban Mahanti</person>
</author>
<title>Comparing Wired-side and Wireless-side WLAN Monitoring Techniques: A Case Study</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of IEEE International Local Computer Networks Workshop on Wireless Local Networks (IEEE WLN)</booktitle>
<month>--10--</month>
<year>2007</year>
<address>Dublin, Ireland</address>
<url>http://pages.cpsc.ucalgary.ca/~amahanti/Papers/WLN2007.pdf</url>
<abstract>Wireless Local Area Networks (WLANs) have become omnipresent: WLANs are 
available at airports, coffee shops, university campuses, corporate 
environments, and homes. This surge in the popularity of WLANs motivates the 
study of how these networks are used. Characterizing WLANs, however, is 
complicated by a number of factors including the geographic diversity of WLAN 
deployments and the need for capturing activity in the wireless environment 
instead of the wired environment. In this paper, we describe our experiences 
with the deployment and use of a remote passive wireless-side measurement 
infrastructure for monitoring usage of WLANs, and compare our results with a 
commonly used wired-side measurement technique. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20071001</pubdate>
</paper>

<paper id="163">
<key>mahanti-remote</key>
<article>
<author>
<person>Aniket Mahanti</person>
<person>Carey Williamson</person>
<person>Martin Arlitt</person>
</author>
<title>Remote Analysis of a Distributed WLAN using Passive Wireless-side Measurement</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>Performance Evaluation</journal>
<year>2007</year>
<volume>64</volume>
<number>9-12</number>
<pages>909-932</pages>
<url>http://pages.cpsc.ucalgary.ca/~amahanti/Papers/Performance2007.pdf</url>
<keyword>IEEE 802.11, Passive measurement, Traffic characterization</keyword>
<month>--10--</month>
<abstract>This paper presents network traffic measurements from a campus-wide wireless 
LAN (WLAN), with the data collected using remote passive wireless-side 
measurement. We used commercially-available monitoring devices to collect 
wireless traffic concurrently from 9 selected locations on the campus WLAN for 
6 weeks. The aggregate trace contains almost 1 billion wireless frames, 
representing the WLAN activity generated by 6775 users and 97 access points. 
Analysis of the dataset identifies similarities and differences in the user 
behaviours across the observed WLAN locations, as well as emerging trends in 
WLAN usage regarding application usage and session mobility. Our study extends 
existing WLAN measurement studies by providing deeper insights into how WLANs 
are used, and by developing models of WLAN usage characteristics that are 
applicable in capacity planning, network testing, and network simulation 
studies. </abstract>
<category>wireless-meas</category>
</article>
<pubdate>20071001</pubdate>
</paper>

<paper id="164">
<key>masala-retransmission</key>
<inproceedings>
<author>
<person>Enrico Masala</person>
<person>Juan Carlos De Martin</person>
</author>
<title>Distortion-optimized retransmission for low-delay robust video communications over 802.11 intervehicle ad hoc networks</title>
<booktitle>VANET '07: Proceedings of the fourth ACM international workshop on Vehicular ad hoc networks</booktitle>
<year>2007</year>
<pages>69-70</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>gatech_vehicular</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287748.1287760</doi>
<url>http://doi.acm.org/10.1145/1287748.1287760</url>
<publisher>ACM Press</publisher>
<keyword>Multimedia, intervehicle communications, v2v, 802.11, videoconference, ARQ</keyword>
<abstract>Wireless Access in Vehicular Environment (WAVE) communications standards have 
recently been approved for trial use and other standards, such as 802.11p, are 
under active development. However, providing reliable communication services in 
the vehicular environment still remains a challenging task. Thus efficient 
solutions are needed to increase robustness and performance. This paper 
presents a new distortion-optimized transmission algorithm which exploits the 
non-uniform importance of multimedia data to optimize the transmission of video 
data captured by on-board cameras to another vehicle in proximity, using ad hoc 
802.11 wireless technology and the H.264 video coding standard. A low delay 
video communication is simulated using actual intervehicle packet loss traces. 
The results show that the proposed system achieves higher quality video 
communication (up to 2 dB PSNR) compared to two reference techniques, i.e. the 
standard MAC-layer retransmission scheme and a delay-constrained retransmission 
technique. </abstract>
<category>wireless-meas,crawdad</category>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="165">
<key>mcdiarmid-nodobo</key>
<misc>
<author>
<person>Alisdair McDiarmid</person>
<person>Stephen Bell</person>
<person>James Irvine</person>
<person>Jamie Banford</person>
</author>
<title>Nodobo: Detailed Mobile Phone Usage Dataset</title>
<howpublished>IET Electronics Letters (under review)</howpublished>
<url>http://nodobo.com/papers/iet-el.pdf</url>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>strath_nodobo</keywords>
<category>wireless-meas</category>
<refnames><refname>strath/nodobo</refname>
</refnames>
</misc>
<pubdate>00000001</pubdate>
</paper>

<paper id="166">
<key>mcnett-access</key>
<article>
<author>
<person>Marvin McNett</person>
<person>Geoffrey M. Voelker</person>
</author>
<title>Access and Mobility of Wireless PDA Users</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>ACM Mobile Computing and Communication Review (MC2R)</journal>
<volume>9</volume>
<number>2</number>
<pages>40-55</pages>
<month>--04--</month>
<year>2005</year>
<url>http://doi.acm.org/10.1145/1072989.1072995</url>
<category>wireless-meas</category>
</article>
<pubdate>20050401</pubdate>
</paper>

<paper id="167">
<key>mcnett-pda</key>
<techreport>
<author>
<person>Marvin McNett</person>
<person>Geoffrey M. Voelker</person>
</author>
<title>Access and Mobility of Wireless PDA Users</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<number>CS2004-0780</number>
<month>--02--</month>
<year>2004</year>
<institution>Department of Computer Science and Engineering, University of California, San Diego</institution>
<url>http://ramp.ucsd.edu/wtd/wtd.pdf</url>
<abstract>In this paper, we analyze the mobility patterns of users of wireless handheld 
PDAs in a campus wireless network using an 11 week trace of wireless network 
activity. Our study has three goals. First, we characterize the high-level 
mobility and access patterns of handheld PDA users and compare these 
characteristics to previous workload mobility studies focused on laptop users. 
Second, we develop two wireless network topology models for use in wireless 
mobility studies: an evolutionary topology model based on user proximity and a 
campus waypoint model that serves as a trace-based complement to the random 
waypoint model. Finally, we use our wireless network topology models as a case 
study to evaluate ad-hoc routing algorithms on the network topologies created 
by the access and mobility patterns of users of modern wireless PDAs. </abstract>
<category>wireless-meas</category>
</techreport>
<pubdate>20040201</pubdate>
</paper>

<paper id="168">
<key>meng-flows</key>
<inproceedings>
<author>
<person>Xiaoqiao (George) Meng</person>
<person>Starsky Wong</person>
<person>Yuan Yuan</person>
<person>Songwu Lu</person>
</author>
<title>Characterizing Flows in Large Wireless Data Networks</title>
<booktitle>Proceedings of the Tenth Annual International Conference on Mobile Computing and Networking</booktitle>
<month>--09--</month>
<year>2004</year>
<publisher>ACM Press</publisher>
<url>http://portal.acm.org/citation.cfm?id=1023720.1023738</url>
<keyword>mobile computing, wireless network, workload characterization, TCP, network flow</keyword>
<abstract>Several studies have recently been performed on wireless university campus 
networks, corporate and public networks. Yet little is known about the 
flow-level characterization in such networks. In this paper, we statistically 
characterize wireless network using a recently-collected trace. For static 
flows, we take a two-tier approach to characterizing the flow arrivals, which 
results a Weibull regression model. We further discover that the static flow 
arrivals in spatial proximity show strong similarity. As for roaming flows, 
they can also be well characterized statistically. We explain the results by 
user behaviors and application demands, and further crossvalidate the modeling 
results by three other traces. Finally, we use two examples to illustrate how 
to apply our models for performance evaluation in the wireless context. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>ibm_watson</keywords>
<keywords>ucsd_sigcomm2001</keywords>
<keywords>stanford_gates</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20040901</pubdate>
</paper>

<paper id="169">
<key>michaut05-application-oriented</key>
<article>
<author>
<person>Fabien Michaut</person>
<person>Francis Lepage</person>
</author>
<title>Application-oriented Network Metrology: Metrics and Active Measurement Tools</title>
<journal>IEEE Communications Surveys &amp; Tutorials</journal>
<month>--04--</month>
<year>2005</year>
<volume>7</volume>
<number>2</number>
<url>http://www.comsoc.org/livepubs/surveys/public/2005/apr/michaut.html</url>
<abstract>The science of communication network metrology consists of measuring the 
performance of networks. This article is a tutorial on application-oriented 
measurement tools and techniques for IP networks. First the principles of 
active measurements are introduced and two important active measurement 
initiatives are presented. Since metrology often requires precision in timing, 
a basic overview related to time in computers and networks will be presented, 
followed by a definition of principal network metrics. Metrics that will be 
discussed are one-way delay, delay variation, round-trip time, packet loss, 
packet reordering, route, and bandwidth. For each parameter, a definition is 
given and related measurement tools and techniques are presented. </abstract>
<category>meta-meas</category>
</article>
<pubdate>20050401</pubdate>
</paper>

<paper id="170">
<key>miluzzo-zigbee_radio</key>
<inproceedings>
<author>
<person>Emiliano Miluzzo</person>
<person>Xiao Zheng</person>
<person>Krist\'of Fodor</person>
<person>Andrew T. Campbell</person>
</author>
<title>Radio Characterization of 802.15.4 and its Impact on the Design of Mobile Sensor Networks</title>
<booktitle>Proceedings of Fifth European Conference on Wireless Sensor Networks (EWSN 2008)</booktitle>
<address>Bologna, Italy</address>
<month>--01--</month>
<year>2008</year>
<url>http://www.cs.dartmouth.edu/~miluzzo/papers/miluzzo_EWSN08.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_zigbee_radio</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/zigbee_radio</refname>
</refnames>
</inproceedings>
<pubdate>20080101</pubdate>
</paper>

<paper id="171">
<key>mishra-mac</key>
<article>
<author>
<person>Arunesh Mishra</person>
<person>Minho Shin</person>
<person>William A. Arbaugh</person>
</author>
<title>An Empirical Analysis of the IEEE 802.11 MAC Layer Handoff Process</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<journal>ACM SIGCOMM Computer Communication Review</journal>
<pages>93-102</pages>
<month>--04--</month>
<year>2003</year>
<volume>33</volume>
<number>2</number>
<publisher>ACM</publisher>
<url>http://www.cs.umd.edu/~mhshin/paper/ACMCCR-Mishra.Shin.Arbaugh.pdf</url>
<category>wireless-meas</category>
</article>
<pubdate>20030401</pubdate>
</paper>

<paper id="172">
<key>moh-healthcare</key>
<inproceedings>
<author><person>Melody Moh</person>
</author>
<title>A Prototype on RFID and Sensor Networks for Elder Healthcare</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-Moh.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="173">
<key>musolesi-car</key>
<article>
<author>
<person>Mirco Musolesi</person>
<person>Cecilia Mascolo</person>
</author>
<title>CAR: Context-aware Adaptive Routing for Delay Tolerant Mobile Networks</title>
<journal>IEEE Transactions on Mobile Computing</journal>
<year>2008</year>
<issn>1536-1233</issn>
<publisher>IEEE Computer Society</publisher>
<address>Los Alamitos, CA, USA</address>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
</article>
<pubdate>20080001</pubdate>
</paper>

<paper id="174">
<key>musolesi-mobility</key>
<inproceedings>
<author>
<person>Mirco Musolesi</person>
<person>Cecilia Mascolo</person>
</author>
<title>A Community Based Mobility Model for Ad Hoc Network Research</title>
<booktitle>Proceedings of the Second International Workshop on Multi-hop Ad Hoc Networks: from Theory to Reality (REALMAN 2006)</booktitle>
<month>--05--</month>
<year>2006</year>
<address>Florence, Italy</address>
<url>http://www.cs.ucl.ac.uk/staff/M.Musolesi/papers/realman06.pdf</url>
<abstract>Validation of mobile ad hoc network protocols relies almost exclusively on 
simulation. The value of the validation is, therefore, highly dependent on how 
realistic the movement models used in the simulations are. Since there is a 
very limited number of available real traces in the public domain, synthetic 
models for movement pattern generation must be used. However, most widely used 
models are currently very simplistic, their focus being ease of implementation 
rather than soundness of foundation. As a consequence, simulation results of 
protocols are often based on randomly generated movement patterns and, 
therefore, may differ considerably from those that can be obtained by deploying 
the system in real scenarios. Movement is strongly affected by the needs of 
humans to socialise or cooperate, in one form or another. Fortunately, humans 
are known to associate in particular ways that can be mathematically modelled 
and that have been studied in social sciences for years. In this paper we 
propose a new mobility model founded on social network theory. The model allows 
collections of hosts to be grouped together in a way that is based on social 
relationships among the individuals. This grouping is then mapped to a 
topographical space, with movements influenced by the strength of social ties 
that may also change in time. We have validated our model with real traces by 
showing that the synthetic mobility traces are a very good approximation of 
human movement patterns. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060501</pubdate>
</paper>

<paper id="175">
<key>musolesi-supporting</key>
<inproceedings>
<author>
<person>Mirco Musolesi</person>
<person>Mattia Piraccini</person>
<person>Kristof Fodor</person>
<person>Antonio Corradi</person>
<person>Andrew T. Campbell</person>
</author>
<title>Supporting Energy-Efficient Uploading Strategies for Continuous Sensing Applications on Mobile Phones</title>
<booktitle>Proceedings of the 8th International Conference on Pervasive Computing (Pervasive 2010)</booktitle>
<pages>355-372</pages>
<year>2010</year>
<editor>P. Flor&#233;en and A. Kr&#252;ger and M. Spasojevic</editor>
<volume>6030</volume>
<series>Lecture Notes in Computer Science</series>
<address>Germany</address>
<month>--05--</month>
<publisher>Springer-Verlag</publisher>
<copyright>Springer-Verlag</copyright>
<url>http://www.cs.st-andrews.ac.uk/~mirco/papers/Pervasive10.pdf</url>
<abstract>Continuous sensing applications (e.g., mobile social networking applications) 
are appearing on new sensor-enabled mobile phones such as the Apple iPhone, 
Nokia and Android phones. These applications present significant challenges to 
the phone's operations given the phone's limited computational and energy 
resources and the need for applications to share real-time continuous sensed 
data with back-end servers. System designers have to deal with a trade-off 
between data accuracy (i.e., application fidelity) and energy constraints in 
the design of uploading strategies between phones and back-end servers. In this 
paper, we present the design, implementation and evaluation of several 
techniques to optimize the information uploading process for continuous sensing 
on mobile phones. We analyze the cases of continuous and intermittent 
connectivity imposed by low-duty cycle design considerations or poor wireless 
network coverage in order to drive down energy consumption and extend the 
lifetime of the phone. We also show how location prediction can be integrated 
into this forecasting framework. We present the implementation and the 
experimental evaluation of these uploading techniques based on measurements 
from the deployment of a continuous sensing application on 20 Nokia N95 phones 
used by 20 people for a period of 2 weeks. Our results show that we can make 
significant energy savings while limiting the impact on the application 
fidelity, making continuous sensing a viable application for mobile phones. For 
example, we show that it is possible to achieve an accuracy of 80\% with 
respect to ground-truth data while saving 60\% of the traffic sent 
over-the-air. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_cenceme</keywords>
<keywords>crawdad</keywords>
<category>wireless-meas,crawdad</category>
<refnames><refname>dartmouth/cenceme</refname>
</refnames>
</inproceedings>
<pubdate>20100501</pubdate>
</paper>

<paper id="176">
<key>naik-bonsai</key>
<inproceedings>
<author>
<person>Vinayak Naik</person>
<person>Emre Ertin</person>
<person>Hongwei Zhang</person>
<person>Anish Arora</person>
</author>
<title>Wireless Testbed Bonsai</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/01-01.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="177">
<key>nasipuri-angle</key>
<inproceedings>
<author>
<person>Asis Nasipuri</person>
<person>Ribal Najjar</person>
</author>
<title>Experimental Evaluation of an Angle Based Indoor Localization System</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/03-05.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="178">
<key>natarajan-bluetooth</key>
<inproceedings>
<author>
<person>Anirudh Natarajan</person>
<person>Mehul Motani</person>
<person>Vikram Srinivasan</person>
</author>
<title>Understanding Urban Interactions from Bluetooth Phone Contact Traces</title>
<booktitle>PAM 2007, 8th Passive and Active Measurement conference</booktitle>
<year>2007</year>
<month>--04--</month>
<pages>115-124</pages>
<url>http://dx.doi.org/10.1007/978-3-540-71617-4_12</url>
<address>Louvain-la-neuve, Belgium</address>
<abstract>The increasing sophistication of mobile devices has enabled several mobile 
social software applications, which are based on opportunistic exchange of data 
amongst devices in proximity of each other. Examples include Delay Tolerant 
Networking (DTN) and PeopleNet. In this context, understanding user 
interactions is essential to designing algorithms which are efficient and 
enhance the user experience. In our experiment, users were handed Bluetooth 
enabled phones and asked to carry them all the time to log information about 
other devices in their proximity. Data was logged over several months, with 
over 350,000 contacts logged and over 10,000 unique devices discovered in this 
period.1 This paper analyzes this data by charactering the distributions of 
metrics such as contact time and inter-pair-contact time, and introducing 
several other important metrics useful for understanding user interactions. We 
find that most metrics follow a power law, except for inter-pair-contact time. 
We also look for patterns in user interactions, with the hope that these can be 
exploited for better algorithm design. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>nus_bluetooth</keywords>
<keywords>crawdad</keywords>
<refnames><refname>nus/bluetooth</refname>
</refnames>
</inproceedings>
<pubdate>20070401</pubdate>
</paper>

<paper id="179">
<key>navda-mobisteer</key>
<inproceedings>
<author>
<person>Vishnu Navda</person>
<person>Anand P. Subramanian</person>
<person>Kannan Dhanasekaran</person>
<person>Andreas Timm-Giel</person>
<person>Samir R. Das</person>
</author>
<title>MobiSteer: Using Steerable Beam Directional Antenna for Vehicular Network Access</title>
<booktitle>Proceedings of the Fifth International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<month>--06--</month>
<year>2007</year>
<address>San Juan, Puerto Rico</address>
<publisher>USENIX Association</publisher>
<url>http://www.wings.cs.sunysb.edu/pubs/mobisteer.pdf</url>
<keyword>Steerable Beam, Phased-array Antenna, Vehicular Internet Access, Fast Handoff</keyword>
<abstract>In this work, we investigate the use of directional antennas and beam steering 
techniques to improve performance of 802.11 links in the context of 
communication between a moving vehicle and roadside APs. To this end, we 
develop a framework called MobiSteer that provides practical approaches to 
perform beam steering. MobiSteer can operate in two modes - cached mode - where 
it uses prior radio survey data collected during \idle" drives, and online 
mode, where it uses probing. The goal is to select the best AP and beam 
combination at each point along the drive given the available information, so 
that the throughput can be maximized. For the cached mode, an optimal algorithm 
for AP and beam selection is developed that factors in all overheads. We 
provide extensive experimental results using a commercially available eight 
element phased-array antenna. In the experiments, we use controlled scenarios 
with our own APs, in two di erent multipath environments, as well as in situ 
scenarios, where we use APs already deployed in an urban region - to 
demonstrate the performance advantage of using MobiSteer over using an 
equivalent omni-directional antenna. We show that MobiSteer improves the 
connectivity duration as well as PHY-layer data rate due to better SNR 
provisioning. In particular, MobiSteer improves the throughput in the 
controlled experiments by a factor of 2 - 4. In in situ experiments, it 
improves the connectivity duration by more than a factor of 2 and average SNR 
by about 15 dB. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>sunysb_mobisteer</keywords>
<keywords>crawdad</keywords>
<refnames><refname>sunysb/mobisteer</refname>
</refnames>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="180">
<key>newport-axioms</key>
<article>
<author>
<person>Calvin Newport</person>
<person>David Kotz</person>
<person>Yougu Yuan</person>
<person>Robert S. Gray</person>
<person>Jason Liu</person>
<person>Chip Elliott</person>
</author>
<title>Experimental Evaluation of Wireless Simulation Assumptions</title>
<journal>SIMULATION: Transactions of The Society for Modeling and Simulation International</journal>
<year>2007</year>
<month>--09--</month>
<volume>83</volume>
<number>9</number>
<pages>643-661</pages>
<publisher>SAGE Publications</publisher>
<url>http://dx.doi.org/10.1177/0037549707085632</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_outdoor</keywords>
<keywords>crawdad</keywords>
<refnames><refname>dartmouth/outdoor</refname>
</refnames>
<abstract>All analytical and simulation research on ad hoc wireless networks must 
necessarily model radio propagation using simplifying assumptions. A growing 
body of research, however, indicates that the behavior of the protocol stack 
may depend significantly on these underlying assumptions. The standard response 
to this problem is a call for more realism in designing radio models. But how 
much realism is enough? This study is the first to approach this question by 
validating simulator performance (both at the physical and application layers) 
with the results of real-world data. Referencing an eXtensive set of 
measurements from a large outdoor routing eXperiment, we start by evaluating 
the relative realism of common assumptions made in radio model design, 
identifying those which provide a reasonable approXimation of reality. Although 
several such investigations have been made for static sensor networks, radio 
behavior in mobile network deployments is a much less-studied topic. We then 
reproduce our eXperimental setup in our simulator, and generate the same 
application-layer metrics under progressively smaller sets of these 
assumptions. By comparing the simulated outcome to the outcome of our 
eXperiment, we are able to discern at what point our balance of simplification 
and realism captures the real behavior of our target environment. </abstract>
</article>
<pubdate>20070901</pubdate>
</paper>

<paper id="181">
<key>ng-evaluation</key>
<inproceedings>
<author>
<person>Anthony C. H. Ng</person>
<person>David Malone</person>
<person>Douglas Leith</person>
</author>
<title>Experimental Evaluation of TCP Performance and Fairness in an 802.11e Test-bed</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-NgMal.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="182">
<key>nicholson-access-point</key>
<inproceedings>
<author>
<person>Anthony J. Nicholson</person>
<person>Yatin Chawathe</person>
<person>Mike Y. Chen</person>
<person>Brian D. Noble</person>
<person>David Wetherall</person>
</author>
<title>Improved access point selection</title>
<booktitle>MobiSys 2006: Proceedings of the 4th international conference on Mobile systems, applications and services</booktitle>
<year>2006</year>
<pages>233-245</pages>
<location>Uppsala, Sweden</location>
<url>http://doi.acm.org/10.1145/1134680.1134705</url>
<doi>http://doi.acm.org/10.1145/1134680.1134705</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
<category>wireless-meas, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umich_virgil</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umich/virgil</refname>
</refnames>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="183">
<key>noda-quantifying</key>
<article>
<author>
<person>Noda, Claro</person>
<person>Prabh, Shashi</person>
<person>Alves, M&#225;rio</person>
<person>Boano, Carlo Alberto</person>
<person>Voigt, Thiemo</person>
</author>
<title>Quantifying the channel quality for interference-aware wireless sensor networks</title>
<journal>SIGBED Rev.</journal>
<volume>8</volume>
<number>4</number>
<month>--12--</month>
<year>2011</year>
<pages>43-48</pages>
<url>http://sigbed.seas.upenn.edu/archives/2011-12/Paper_5.pdf</url>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<keywords>ISM bands</keywords>
<keywords>channel quality</keywords>
<keywords>dynamic resource adaptation</keywords>
<keywords>interference</keywords>
<keywords>wireless sensor networks</keywords>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>cister_rssi</keywords>
<category>wireless-meas</category>
<refnames><refname>cister/rssi</refname>
</refnames>
</article>
<pubdate>20111201</pubdate>
</paper>

<paper id="184">
<key>pan-faultyap</key>
<inproceedings>
<author>
<person>H.J. Pan</person>
<person>S. Keshav</person>
</author>
<title>Detection and Repair of Faulty Access Points</title>
<booktitle>Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2006)</booktitle>
<month>--04--</month>
<year>2006</year>
<address>Las Vegas, NV, USA</address>
<url>http://blizzard.cs.uwaterloo.ca/keshav/home/Papers/data/05/faults.pdf</url>
<abstract>In large-scale infrastructure wireless networks several access points (APs) may 
be unusable at any given moment in time. Unlike completely failed APs, whose 
failure can be detected by probes to their wired interface, an AP with a faulty 
wireless interface or whose antenna has been accidentally shielded can only be 
diagnosed by the actual use of the wireless interface for data communication. 
We present several algorithms that detect such failed access points by online 
analysis of AP usage logs. In particular, we demonstrate that we can exploit 
device mobility to detect faulty APs. We also present efficient heuristics to 
select a path for a technician to repair failed access points. We evaluate our 
algorithms using actual log files from an infrastructure network at Dartmouth 
College. We find that our best algorithm is able to detect nearly 90% of failed 
access points simply by processing log files. Compared to a naive approach, our 
algorithm has more than six times fewer false positives. We are also able to 
construct tours that are up to an order of magnitude more effective that a 
straightforward greedy approach. Our algorithms require no modifications to 
either APs or devices. We believe that these properties make our work 
immediately applicable to real-world scenarios. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="185">
<key>pang03-high-level</key>
<inproceedings>
<author>
<person>Ruoming Pang</person>
<person>Vern Paxson</person>
</author>
<title>A High-level Programming Environment for Packet Trace Anonymization and Transformation</title>
<booktitle>Proceedings of ACM SIGCOMM 2003</booktitle>
<pages>339-351</pages>
<month>--08--</month>
<year>2003</year>
<address>Karlsruhe, Germany</address>
<url>http://www.acm.org/sigcomm/sigcomm2003/papers/p339-pang.pdf</url>
<abstract>Packet traces of operational Internet traffic are invaluable to network 
research, but public sharing of such traces is severely limited by the need to 
first remove all sensitive information. Current trace anonymization technology 
leaves only the packet headers intact, completely stripping the contents; to 
our knowledge, there are no publicly available traces of any significant size 
that contain packet payloads. We describe a new approach to transform and 
anonymize packet traces. Our tool provides high-level language support for 
packet transformation, allowing the user to write short policy scripts to 
express sophisticated trace transformations. The resulting scripts can 
anonymize both packet headers and payloads, and can perform application-level 
transformations such as editing HTTP or SMTP headers, replacing the content of 
Web items with MD5 hashes, or altering filenames or reply codes that match 
given patterns. We discuss the critical issue of verifying that anonymizations 
are both correctly applied and correctly specified, and experiences with 
anonymizing FTP traces from the Lawrence Berkeley National Laboratory for 
public release. </abstract>
<category>meta-meas</category>
</inproceedings>
<pubdate>20030801</pubdate>
</paper>

<paper id="186">
<key>pang-devil</key>
<article>
<author>
<person>Ruoming Pang</person>
<person>Mark Allman</person>
<person>Vern Paxson</person>
<person>Jason Lee</person>
</author>
<title>The Devil and Packet Trace Anonymization</title>
<journal>ACM Computer Communication Review</journal>
<month>--01--</month>
<year>2006</year>
<volume>36</volume>
<number>1</number>
<pages>29-38</pages>
<url>http://www.icir.org/mallman/papers/devil-ccr-jan06.pdf</url>
<abstract>Releasing network measurement data - including packet traces - to the research 
community is a virtuous activity that promotes solid research. However, in 
practice, releasing anonymized packet traces for public use entails many more 
vexing considerations than just the usual notion of how to scramble IP 
addresses to preserve privacy. Publishing traces requires carefully balancing 
the security needs of the organi- zation providing the trace with the research 
usefulness of the anonymized trace. In this paper we recount our experiences in 
(i) securing permission from a large site to release packet header traces of 
the site's internal traffic, (ii) implementing the corresponding anonymization 
policy, and (iii) validating its correctness. We present a general tool, 
tcpmkpub, for anonymizing traces, discuss the process used to determine the 
particular anonymization policy, and describe the use of meta- data 
accompanying the traces to provide insight into features that have been 
obfuscated by anonymization. </abstract>
<category>meta-meas</category>
</article>
<pubdate>20060101</pubdate>
</paper>

<paper id="187">
<key>pang-fingerprinting</key>
<inproceedings>
<author>
<person>Jeffrey Pang</person>
<person>Ben Greenstein</person>
<person>Ramakrishna Gummadi</person>
<person>Srinivasan Seshan</person>
<person>David Wetherall</person>
</author>
<title>802.11 user fingerprinting</title>
<booktitle>MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking</booktitle>
<year>2007</year>
<pages>99-110</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>uw_sigcomm2004</keywords>
<keywords>tools_process_pcap_Wifipcap</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287853.1287866</doi>
<url>http://doi.acm.org/10.1145/1287853.1287866</url>
<publisher>ACM Press</publisher>
<abstract>The ubiquity of 802.11 devices and networks enables anyone to track our every 
move with alarming ease. Each 802.11 device transmits a globally unique and 
persistent MAC address and thus is trivially identifiable. In response, recent 
research has proposed replacing such identifiers with pseudonyms (i.e., 
temporary, unlinkable names). In this paper, we demonstrate that pseudonyms are 
insufficient to prevent tracking of 802.11 devices because implicit 
identifiers, or identifying characteristics of 802.11 traffic, can identify 
many users with high accuracy. For example, even without unique names and 
addresses, we estimate that an adversary can identify 64% of users with 90% 
accuracy when they spend a day at a busy hot spot. We present an automated 
procedure based on four previously unrecognized implicit identifiers that can 
identify users in three real 802.11 traces even when pseudonyms and encryption 
are employed. We find that the majority of users can be identified using our 
techniques, but our ability to identify users is not uniform; some users are 
not easily identifiable. Nonetheless, we show that even a single implicit 
identifier is sufficient to distinguish many users. Therefore, we argue that 
design considerations beyond eliminating explicit identifiers (i.e., unique 
names and addresses), must be addressed in order to prevent user tracking in 
wireless networks. </abstract>
<refnames><refname>tools/process/pcap/Wifipcap</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="188">
<key>pang-wifi-reports</key>
<inproceedings>
<author>
<person>Jeffrey Pang</person>
<person>Ben Greenstein</person>
<person>Michael Kaminsky</person>
<person>Damon McCoy</person>
<person>Srinivasan Seshan</person>
</author>
<title>Wifi-Reports: Improving Wireless Network Selection with Collaboration</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>cmu_hotspot</keywords>
<keywords>tools_collect_802.11_Wifi-Scanner</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the Seventh International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<month>--06--</month>
<year>2009</year>
<address>Krakow, Poland</address>
<publisher>USENIX Association</publisher>
<url>http://www.cs.cmu.edu/~jeffpang/papers/mobisys09-wifireports.pdf</url>
<abstract>Wi-Fi clients can obtain much better performance at some commercial hotspots 
than at others. Unfortunately, there is currently no way for users to determine 
which hotspot access points (APs) will be sufficient to run their applications 
be- fore purchasing access. To address this problem, this paper presents 
Wifi-Reports, a collaborative service that provides Wi-Fi clients with 
historical information about AP perfor- mance and application support. The key 
research chal- lenge in Wifi-Reports is to obtain accurate user-submitted 
reports. This is challenging because two conflicting goals must be addressed in 
a practical system: preserving the pri- vacy of users' reports and limiting 
fraudulent reports. We introduce a practical cryptographic protocol that 
achieves both goals, and we address the important engineering chal- lenges in 
building Wifi-Reports. Using a measurement study of commercial APs in Seattle, 
we show that Wifi-Reports would improve performance over previous AP selection 
ap- proaches in 30\%-60\% of locations. </abstract>
<category>wireless-meas,crawdad</category>
<refnames><refname>cmu/hotspot</refname>
<refname>tools/collect/802.11/Wifi-Scanner</refname>
</refnames>
</inproceedings>
<pubdate>20090601</pubdate>
</paper>

<paper id="189">
<key>papadogkonas-ubiquitous</key>
<inproceedings>
<author>
<person>D. Papadogkonas</person>
<person>G. Roussos</person>
<person>M. Levene</person>
</author>
<title>A Navigation Engine for Ubiquitous Computing Environments</title>
<booktitle>Proceedings of the 4th Uk Ubinet Workshop</booktitle>
<month>--07--</month>
<year>2006</year>
<address>London, UK</address>
<url>http://www.dcs.bbk.ac.uk/~dikaios/Publications/UK-UbiNet2006/UK-UbiNet2006.pdf</url>
<abstract>Ubiquitous computing linked physical and virtual spaces, so new tools are 
required to assist navigation in such environments. We propose a navigation 
engine for identifying navigation patterns from prerecorded user trails, 
provide information about the usage of the environment and assist navigation in 
unfamiliar environments by providing best available trails. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060701</pubdate>
</paper>

<paper id="190">
<key>papadopouli-characterizing</key>
<inproceedings>
<author>
<person>Maria Papadopouli</person>
<person>Haipeng Shen</person>
<person>Manolis Spanakis</person>
</author>
<title>Characterizing the duration and association patterns of wireless access in a campus</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 11th European Wireless Conference</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Nicosia, Cyprus</address>
<url>http://www.cs.unc.edu/~maria/eu05.pdf</url>
<keyword>mobile computing, wireless network, workload characterization, association modeling</keyword>
<abstract>Our goal is to characterize the access patterns in a IEEE802.11 infrastructure. 
This can be beneficial in many domains, including coverage planning, resource 
reservation, supporting location-dependent applications and applications with 
real-time constraints, and producing models for simulations. We conducted an 
extensive measurement study of wireless users and their association patterns on 
a major university campus using the IEEE802.11 wireless infrastructure. We 
characterized and analyzed the wireless access pattern based on several 
parameters such as mobility, session and visit durations. We show that the 
mobility and building type affect the session and visit durations. As the 
mobility increases, the visit duration tends to decrease stochastically. The 
opposite happens in the case of the session duration. Moreover, there exist 
different stochastic orders among visit durations of different building types 
when conditioning on session mobility. A family of BiPareto distributions can 
model the visit and session duration. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="191">
<key>papadopouli-modeling</key>
<inproceedings>
<author>
<person>Maria Papadopouli</person>
<person>Haipeng Shen</person>
<person>Manolis Spanakis</person>
</author>
<title>Modeling client arrivals at access points in wireless campus-wide networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 14th IEEE Workshop on Local and Metropolitan Area Networks</booktitle>
<month>--09--</month>
<year>2005</year>
<address>Crete, Greece</address>
<url>http://www.cs.unc.edu/~maria/lanman05-A.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050901</pubdate>
</paper>

<paper id="192">
<key>papadopouli-short</key>
<inproceedings>
<author>
<person>Maria Papadopouli</person>
<person>Haipeng Shen</person>
<person>Elias Raftopoulos</person>
<person>Manolis Ploumidis</person>
<person>Felix Hernandez-Campos</person>
</author>
<title>Short-term traffic forecasting in a campus-wide wireless network</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 16th Annual IEEE International Symposium on Personal Indoor and Mobile Radio Communications</booktitle>
<month>--09--</month>
<year>2005</year>
<address>Berlin, Germany</address>
<url>http://www.cs.unc.edu/~maria/pimrc05-A.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050901</pubdate>
</paper>

<paper id="193">
<key>papagiannaki-home</key>
<inproceedings>
<author>
<person>Konstantina Papagiannaki</person>
<person>Mark Yarvis</person>
<person>W. Steven Conner</person>
</author>
<title>Experimental Characterization of Home Wireless Networks and Design Implications</title>
<booktitle>Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM)</booktitle>
<month>--04--</month>
<year>2006</year>
<address>Barcelona, Spain</address>
<url>http://www.cambridge.intel-research.net/~kpapagia/papers/homenet.pdf</url>
<abstract>Anecdotal evidence suggests that home wireless networks may be unpredictable 
despite their limited size. In this work, we deploy six-node wireless testbeds 
in three houses in the United States and the United Kingdom.We examine the 
quality of links in home wireless networks and the effect of (i) transmission 
rate, (ii) transmission power, (iii) node location, (iv) type of house, and (v) 
802.11 technology. We provide empirical evidence suggesting that homes are 
challenging environments for wireless communication.Wireless links in the home 
are highly asymmetric and heavily influenced by precise node location, 
transmission power, and encoding rate, rather than physical distance between 
nodes. In our measurements, many links were unable to utilize the maximum 
transmission rate of the deployed 802.11 technology, and a few provided no 
connectivity at all. These results suggest that creating an AP-based topology 
with maximum coverage and throughput in this environment is challenging. Our 
findings have implications on the design of future home wireless networks and 
requirements for future wifi-enabled consumer electronic devices. We show that 
coverage and performance can be improved using a multi-hop topology, implying 
that mesh capabilities may actually be needed in consumer electronics for 
seamless connectivity across the home. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>intel_home</keywords>
<keywords>crawdad</keywords>
<refnames><refname>intel/home</refname>
</refnames>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="194">
<key>parris-facebook</key>
<inproceedings>
<author>
<person>Parris, Iain</person>
<person>Ben Abdesslem, Fehmi</person>
<person>Henderson, Tristan</person>
</author>
<title>Facebook or Fakebook?: The effect of simulation on location privacy user studies</title>
<booktitle>Proceedings of the Privacy and Usability Methods Pow-Wow (PUMP)</booktitle>
citeulike-article-id={7694010},
citeulike-linkout-0={http://scone.cs.st-andrews.ac.uk/pump2010/papers/parris.pdf},
<location>Dundee, UK</location>
<month>--09--</month>
 posted-at = {2010-08-24 11:33:34},
<priority>0</priority>
<publisher>British Computer Society</publisher>
<url>http://scone.cs.st-andrews.ac.uk/pump2010/papers/parris.pdf</url>
<year>2010</year>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>st_andrews_locshare</keywords>
<category>wireless-meas, crawdad</category>
<refnames><refname>st_andrews/locshare</refname>
</refnames>
</inproceedings>
<pubdate>20100901</pubdate>
</paper>

<paper id="195">
<key>patwari-relative</key>
<misc>
<author>
<person>N. Patwari</person>
<person>A. O. Hero</person>
<person>M. Perkins</person>
<person>N. S. Correal</person>
<person>R. J. O'Dea</person>
</author>
<title>Relative location estimation in wireless sensor networks</title>
<journal>IEEE Transactions on Signal Processing</journal>
<volume>51</volume>
<number>8</number>
<month>--08--</month>
<year>2007</year>
<pages>2137-2148</pages>
<publisher>IEEE Computer Society</publisher>
<url>http://www.ece.utah.edu/~npatwari/pubs/patwari03-print.pdf</url>
<category>wireless-meas</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>utah_CIR</keywords>
<keywords>crawdad</keywords>
<refnames><refname>utah/CIR</refname>
</refnames>
</misc>
<pubdate>20070801</pubdate>
</paper>

<paper id="196">
<key>patwari-signatures</key>
<inproceedings>
<author>
<person>Neal Patwari</person>
<person>Sneha K. Kasera</person>
</author>
<title>Robust location distinction using temporal link signatures</title>
<booktitle>MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking</booktitle>
<year>2007</year>
<pages>111-122</pages>
<address>Montreal, Quebec, Canada</address>
<doi>http://doi.acm.org/10.1145/1287853.1287867</doi>
<url>http://doi.acm.org/10.1145/1287853.1287867</url>
<publisher>ACM Press</publisher>
<abstract>The ability of a receiver to determine when a transmitter has changed location 
is important for energy conservation in wireless sensor networks, for physical 
security of radio- tagged objects, and for wireless network security in detec- 
tion of replication attacks. In this paper, we propose us- ing a measured 
temporal link signature to uniquely identify the link between a transmitter and 
a receiver. When the transmitter changes location, or if an attacker at a 
diÂ®erent location assumes the identity of the transmitter, the pro- posed link 
distinction algorithm reliably detects the change in the physical channel. This 
detection can be performed at a single receiver or collaboratively by multiple 
receivers. We record over 9,000 link signatures at diÂ®erent locations and over 
time to demonstrate that our method signiÂ¯cantly increases the detection rate 
and reduces the false alarm rate, in comparison to existing methods. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>utah_CIR</keywords>
<keywords>crawdad</keywords>
<refnames><refname>utah/CIR</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="197">
<key>paxson04-strategies</key>
<inproceedings>
<author><person>Vern Paxson</person>
</author>
<title>Strategies for Sound Internet Measurement</title>
<booktitle>Proceedings of the 4th Internet Measurement Conference</booktitle>
<pages>263-271</pages>
<month>--10--</month>
<year>2004</year>
<address>Taormina, Sicily, Italy</address>
<url>http://www.icir.org/vern/papers/meas-strategies-imc04.pdf</url>
<abstract>Conducting an Internet measurement study in a sound fashion can be much more 
difficult than it might first appear. We present a number of strategies drawn 
from experiences for avoiding or overcoming some of the pitfalls. In 
particular, we discuss dealing with errors and inaccuracies; the importance of 
associating meta-data with measurements; the technique of calibrating 
measurements by examining outliers and testing for consistencies; difficulties 
that arise with large-scale measurements; the utility of developing a 
discipline for reliably reproducing analysis results; and issues with making 
datasets publicly available. We conclude with thoughts on the sorts of tools 
and community practices that can assist researchers with conducting sound 
measurement studies. </abstract>
<category>meta-meas</category>
</inproceedings>
<pubdate>20041001</pubdate>
</paper>

<paper id="198">
<key>peddemors-density-estimation</key>
<inproceedings>
<author>
<person>A. Peddemors</person>
<person>H. Eertink</person>
<person>I. Niemegeers</person>
</author>
<title>Density Estimation for Out-of-Range Events on Personal Mobile Devices</title>
<booktitle>the 1st ACM SIGMOBILE International Workshop on Mobility Models for Networking Research (MobilityModels'08)</booktitle>
<year>2008</year>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>novay_cosphere</keywords>
<keywords>crawdad</keywords>
<refnames><refname>novay/cosphere</refname>
</refnames>
</inproceedings>
<pubdate>20080001</pubdate>
</paper>

<paper id="199">
<key>pellegrini-disconnected</key>
<inproceedings>
<author>
<person>F. De Pellegrini</person>
<person>D. Miorandi</person>
<person>I. Carreras</person>
<person>I. Chlamtac</person>
</author>
<title>A Graph-Based Model for Disconnected Ad Hoc Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 26th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<month>--03--</month>
<year>2007</year>
<address>Anchorage, Alaska</address>
<publisher>IEEE</publisher>
<category>wireless-meas,crawdad</category>
</inproceedings>
<pubdate>20070301</pubdate>
</paper>

<paper id="200">
<key>phillips-robust</key>
<inproceedings>
<author>
<person>Caleb Phillips</person>
<person>Russell Senior</person>
<person>Douglas Sicker</person>
<person>Dirk Grunwald</person>
</author>
<title>Robust Coverage and Performance Testing for Large-Area Wireless Networks</title>
<booktitle>AccessNets</booktitle>
<pages>457-469</pages>
<year>2009</year>
<editor>Wang, Chonggang and Akan, Ozgur and Bellavista, Paolo and Cao, Jiannong and Dressler, Falko and Ferrari, Domenico and Gerla, Mario and Kobayashi, Hisashi and Palazzo, Sergio and Sahni, Sartaj and Shen, Xuemin (Sherman) and Stan, Mircea and Xiaohua, Jia and Zomaya, Albert and Coulson, Geoffrey</editor>
<volume>6</volume>
<series>Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering</series>
<address>Germany</address>
<url>http://www.unwirepdx-watch.org/files/accessnets08.pdf</url>
<publisher>Springer-Verlag</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>pdx_metrofi</keywords>
<category>wireless-meas, crawdad</category>
<refnames><refname>pdx/metrofi</refname>
</refnames>
</inproceedings>
<pubdate>20090001</pubdate>
</paper>

<paper id="201">
<key>phillips-wlan</key>
<inproceedings>
<author>
<person>Caleb Phillips</person>
<person>Suresh Singh</person>
</author>
<title>Analysis of WLAN traffic in the wild</title>
<booktitle>Proceedings of IFIP-Networking 2007</booktitle>
<month>--05--</month>
<year>2007</year>
<url>http://www.cs.pdx.edu/~singh/ftp/networking07.pdf</url>
<address>Atlanta, Georgia</address>
<keyword>measurement,WLAN,passive monitoring,traffic modeling</keyword>
<abstract>In this paper, we analyze traffic seen at public WLANs "in the wild" where we 
do not have access to any of the backend infrastructure. We study six such 
traces collected around Portland, Oregon and conduct an analysis of fine time 
scale (second or fraction of a second) packet, flow, and error characteristics 
of these networks. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>pdx_vwave</keywords>
<keywords>crawdad</keywords>
<refnames><refname>pdx/vwave</refname>
</refnames>
</inproceedings>
<pubdate>20070501</pubdate>
</paper>

<paper id="202">
<key>piorkowski-mobile-network-model</key>
<inproceedings>
<author>
<person>Michal Piorkowski</person>
<person>Natasa Sarafijanovoc-Djukic</person>
<person>Matthias Grossglauser</person>
</author>
<title>A Parsimonious Model of Mobile Partitioned Networks with Clustering</title>
<booktitle>The First International Conference on COMmunication Systems and NETworkS (COMSNETS)</booktitle>
<address>Bangalore, India</address>
<location>Bangalore, India</location>
<year>2009</year>
<month>--01--</month>
<url>http://icapeople.epfl.ch/grossglauser/Papers/comsnets09.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>epfl_mobility</keywords>
<keywords>crawdad</keywords>
<refnames><refname>epfl/mobility</refname>
</refnames>
</inproceedings>
<pubdate>20090101</pubdate>
</paper>

<paper id="203">
<key>pitkanen-redundancy</key>
<inproceedings>
<author>
<person>Mikko Pitkanen</person>
<person>Joerg Ott</person>
</author>
<title>Redundancy and Distributed Caching in Mobile DTNs</title>
<booktitle>Proceedings of the ACM SIGCOMM MobiArch Workshop</booktitle>
<month>--08--</month>
<year>2007</year>
<address>Kyoto, Japan</address>
<url>http://www.sigcomm.org/sigcomm2007/mobiarch/Pitkanen_CachingDTN.pdf</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20070801</pubdate>
</paper>

<paper id="204">
<key>policroniades-human-networks</key>
<inproceedings>
<author>
<person>Calicrates Policroniades</person>
<person>Pablo Vidales</person>
<person>Martin Roth</person>
<person>Daniel Kreienb&#252;hl</person>
</author>
<title>Data management in human networks</title>
<keywords>challenged networks</keywords>
<keywords>data management</keywords>
<booktitle>CHANTS '07: Proceedings of the second workshop on Challenged networks CHANTS</booktitle>
<year>2007</year>
<pages>83-90</pages>
<address>Montreal, Quebec, Canada</address>
<doi>http://doi.acm.org/10.1145/1287791.1287807</doi>
<url>http://doi.acm.org/10.1145/1287791.1287807</url>
<publisher>ACM Press</publisher>
<abstract>In this paper we study the use of a semantically rich storage model to fulfill 
the data transmission requirements of challenged networking environments, which 
are characterised by long delays and frequent communication disruptions. 
Practical experience shows us that the highly successful data abstractions of 
mainstream storage systems (e.g. monolithic file representation) operate poorly 
in emergent networking environments such as Delay Tolerant Networks (DTNs); 
short contact times do not allow for complete file or bundle transmissions. We 
have ported and integrated two systems in order to provide a solution that 
overcomes many of the data transmission challenges of DTNs: a semantically rich 
storage system (Datom) and a network framework capable of exploiting this 
augmented expressive power (Haggle). Our solution, Bedouin, enables both 
systems to run on resource-constrained devices. It facilitates meaningful data 
exchanges in challenged networks supporting the principle of 
infrastructure-independent networking, and exploiting human mobility and 
opportunistic connectivity. The design and function of a proof-of-concept 
Bedouin-based peer-topeer file sharing application for human networks, called 
Caravan, is included. Experimental results demonstrate that our solution 
enables applications to work correctly in spite of intermittent data exchanges 
and disruptions while maximising the amount of useful data delivered to 
applications. </abstract>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="205">
<key>portoles-comeras-multi</key>
<inproceedings>
<author>
<person>Marc Portoles-Comeras</person>
<person>Josep Mangues-Bafalluy</person>
<person>Manuel Requena-Esteso</person>
</author>
<title>Multi-Radio Based Active and Passive Wireless Network Measurements</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/01-03.doc</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="206">
<key>rahmati-context</key>
<inproceedings>
<author>
<person>Ahmad Rahmati</person>
<person>Lin Zhong</person>
</author>
<title>Context for Wireless: Context-sensitive energy-efficient wireless data transfer</title>
<booktitle>Proceedings of the Fifth International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<month>--06--</month>
<year>2007</year>
<url>http://doi.acm.org/10.1145/1247660.1247681</url>
<address>San Juan, Puerto Rico</address>
<publisher>USENIX Association</publisher>
<keyword>Energy-efficient wireless, multiple wireless interfaces, contextfor-wireless</keyword>
<abstract>Ubiquitous connectivity on mobile devices will enable numerous new applications 
in healthcare and multimedia. We set out to check how close we are towards 
ubiquitous connectivity in our daily life. The findings from our recent 
field-collected data from an urban university population show that while 
network availability is decent, the energy cost of network interfaces poses a 
great challenge. Based on our findings, we propose to leverage the 
complementary strength of Wi-Fi and cellular networks by choosing wireless 
interfaces for data transfers based on network condition estimation. We show 
that an ideal selection policy can more than double the battery lifetime of a 
commercial mobile phone, and the improvement varies with data transfer patterns 
and Wi-Fi availability. We formulate the selection of wireless interfaces as a 
statistical decision problem. The key to attaining the potential battery 
improvement is to accurately estimate Wi-Fi network conditions without powering 
up its network interface. We explore the use of different context information, 
including time, history, cellular network conditions, and device motion, for 
this purpose. We consequently devise algorithms that can effectively learn from 
context information and estimate the probability distribution of Wi-Fi network 
conditions. Simulations based on field-collected traces show that our 
algorithms can improve the average battery lifetime of a commercial mobile 
phone for a three-channel electrocardiogram (ECG) reporting application by 39%, 
very close to the theoretical upper bound of 42%. Finally, our field validation 
of our most simple algorithm demonstrates a 35% improvement in battery 
lifetime. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>rice_context</keywords>
<keywords>crawdad</keywords>
<refnames><refname>rice/context</refname>
</refnames>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="207">
<key>ramachandran-framework</key>
<inproceedings>
<author>
<person>Krishna Ramachandran</person>
<person>Kevin Almeroth</person>
<person>Elizabeth Belding-Royer</person>
</author>
<title>A Novel Framework for the Management of Large-scale Wireless Network Testbeds</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Ramachandran.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="208">
<key>ramachandran-mesh</key>
<inproceedings>
<author>
<person>Krishna Ramachandran</person>
<person>Irfan Sheriff</person>
<person>Elizabeth Belding</person>
<person>Kevin Almeroth</person>
</author>
<title>Routing Stability in Static Wireless Mesh Networks</title>
<booktitle>Proceedings of the eighth Passive and Active Measurement conference</booktitle>
<month>--04--</month>
<year>2007</year>
<address>Louvain-la-neuve, Belgium</address>
<url>http://moment.cs.ucsb.edu/meshnet/datasets/pam.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ucsb_meshnet</keywords>
<keywords>crawdad</keywords>
<refnames><refname>ucsb/meshnet</refname>
</refnames>
</inproceedings>
<pubdate>20070401</pubdate>
</paper>

<paper id="209">
<key>ramachandran-spatial</key>
<inproceedings>
<author>
<person>Kishore Ramachandran</person>
<person>Sanjit Kaul</person>
<person>Suhas Mathur</person>
<person>Marco Gruteser</person>
<person>Ivan Seskar</person>
</author>
<title>Towards Large-Scale Mobile Network Emulation Through Spatial Switching on a Wireless Grid</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-RamKau.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="210">
<key>rayanchu-airshark</key>
<inproceedings>
<author>
<person>Shravan Rayanchu</person>
<person>Ashish Patro</person>
<person>Suman Banerjee</person>
</author>
<title>Airshark: Detecting Non-WiFi RF Devices using Commodity WiFi Hardware</title>
<booktitle>Proceedings of the 2011 Internet Measurement Conference</booktitle>
<year>2011</year>
<address>Berlin, Germany</address>
<url>http://mobilityfirst.winlab.rutgers.edu/documents/Airshark.pdf</url>
<publisher>ACM</publisher>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>wisc_airshark</keywords>
<category>wireless-meas</category>
<refnames><refname>wisc/airshark</refname>
</refnames>
</inproceedings>
<pubdate>20110001</pubdate>
</paper>

<paper id="211">
<key>rhee-levy-walk</key>
<inproceedings>
<author>
<person>Injong Rhee</person>
<person>Minsu Shin</person>
<person>Seongik Hong</person>
<person>Kyunghan Lee</person>
<person>Song Chong</person>
</author>
<title>On the Levy-walk Nature of Human Mobility</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>ncsu_mobilitymodels</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the 27th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<month>--04--</month>
<year>2008</year>
<address>Arizona, USA</address>
<publisher>IEEE</publisher>
<url>http://netsrv.csc.ncsu.edu/export/infocom2008_mobility_final.pdf</url>
<category>wireless-meas,crawdad</category>
<refnames><refname>ncsu/mobilitymodels</refname>
</refnames>
</inproceedings>
<pubdate>20080401</pubdate>
</paper>

<paper id="212">
<key>robinson-experimenting</key>
<inproceedings>
<author>
<person>Joshua Robinson</person>
<person>Konstantina Papagiannaki</person>
<person>Christophe Diot</person>
<person>Xingang Guo</person>
<person>Lakshman Krishnamurthy</person>
</author>
<title>Experimenting with a Multi-Radio Mesh Networking Testbed</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Robinson.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="213">
<key>rodrig-hotspot</key>
<inproceedings>
<author>
<person>Maya Rodrig</person>
<person>Charles Reis</person>
<person>Ratul Mahajan</person>
<person>David Wetherall</person>
<person>John Zahorian</person>
</author>
<title>Measurement-based Characterization of 802.11 in a Hotspot Setting</title>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-RodRei.pdf</url>
<category>crawdad,wireless-meas</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>uw/sigcomm2004</keywords>
<keywords>crawdad</keywords>
<refnames><refname>uw/sigcomm2004</refname>
</refnames>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="214">
<key>roth-topologies</key>
<inproceedings>
<author>
<person>Martin Roth</person>
<person>Pablo Vidales</person>
</author>
<title>Defining and Exploiting Network Topologies in Human Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>crawdad</keywords>
<booktitle>Proceedings of the IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)</booktitle>
<month>--06--</month>
<year>2007</year>
<address>Espoo, Finland</address>
<pages>1-6</pages>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="215">
<key>sani-directional</key>
<inproceedings>
<author>
<person>Amiri Sani, Ardalan</person>
<person>Zhong, Lin</person>
<person>Sabharwal, Ashutosh</person>
</author>
<title>Directional antenna diversity for mobile devices: characterizations and solutions</title>
<booktitle>Proceedings of the 16th Annual International Conference on Mobile Computing and Networking</booktitle>
<series>MobiCom '10</series>
<year>2010</year>
<location>Chicago, Illinois, USA</location>
<pages>221-232</pages>
<numpages>12</numpages>
<url>http://www.owlnet.rice.edu/~aa15/papers/MOBICOM10.pdf</url>
<doi>http://doi.acm.org/10.1145/1859995.1860021</doi>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>rice_midas</keywords>
<keywords>crawdad</keywords>
<category>wireless-meas,crawdad</category>
<refnames><refname>rice/midas</refname>
</refnames>
</inproceedings>
<pubdate>20100001</pubdate>
</paper>

<paper id="216">
<key>sarat-malware</key>
<inproceedings>
<author>
<person>Sandeep Sarat</person>
<person>Andreas Terzis</person>
</author>
<title>On Using Mobility to Propagate Malware</title>
<booktitle>Proceedings of the 5th Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt 2007)</booktitle>
<month>--04--</month>
<year>2007</year>
<address>Limassol, Cyprus</address>
<url>http://www.cs.jhu.edu/~sarat/WiOPT07.pdf</url>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20070401</pubdate>
</paper>

<paper id="217">
<key>savic-packaging</key>
<inproceedings>
<author>
<person>Dragan Savi&#263;</person>
<person>Matev&#382; Pusti&#353;ek</person>
<person>Francesco Potort&#236;</person>
</author>
<title>A tool for packaging and exchanging simulation results</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>valuetools '06: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools</booktitle>
<year>2006</year>
<pages>60</pages>
<location>Pisa, Italy</location>
<url>http://doi.acm.org/10.1145/1190095.1190172</url>
<doi>http://doi.acm.org/10.1145/1190095.1190172</doi>
<publisher>ACM Press</publisher>
<address>New York, NY, USA</address>
<category>wireless-meas, crawdad</category>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="218">
<key>scheuerman-synchronization</key>
<article>
<author>
<person>Björn Scheuermann</person>
<person>Wolfgang Kiess</person>
<person>Magnus Roos</person>
<person>Florian Jarre</person>
<person>Martin Mauve</person>
</author>
<title>On the Time Synchronization of Distributed Log Files in Networks with Local Broadcast Media</title>
<year>2008</year>
<journal>IEEE/ACM Transactions on Networking</journal>
<publisher>IEEE/ACM</publisher>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_process_pcap_pcapsync</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/process/pcap/pcapsync</refname>
</refnames>
</article>
<pubdate>20080001</pubdate>
</paper>

<paper id="219">
<key>schulman-fidelity</key>
<inproceedings>
<author>
<person>Aaron Schulman</person>
<person>Dave Levin</person>
<person>Neil Spring</person>
</author>
<title>On the Fidelity of 802.11 Packet Traces</title>
<booktitle>PAM 2008, 9th Passive and Active Measurement conference</booktitle>
<year>2008</year>
<month>--04--</month>
<pages>132-141</pages>
<url>http://www.cs.umd.edu/projects/wifidelity/papers/pam08-fidelity.pdf</url>
<address>Cleveland, Ohio</address>
<abstract>Packet traces from 802.11 wireless networks are incomplete both fundamentally, 
because antennas do not pick up every transmission, and practically, because 
the hardware and software of collection may be under provisioned. One strategy 
toward improving the completeness of a trace of wireless network traffic is to 
deploy several monitors; these are likely to capture (and miss) different 
packets. Merging these traces into a single, coherent view requires inferring 
access point (AP) and client behavior; these inferences introduce errors. In 
this paper, we present methods to evaluate the fidelity of merged and 
independent wireless network traces. We show that wireless traces contain 
sufficient information to measure their completeness and clock accuracy. 
Specifically, packet sequence numbers indicate when packets have been dropped, 
and AP beacon intervals help determine the accuracy of packet timestamps. We 
also show that trace completeness and clock accuracy can vary based on load. We 
apply these metrics to evaluate fidelity in two ways: (1) to visualize the 
completeness of different 802.11 traces, which we show with several traces 
available on CRAWDAD and (2) to estimate the uncertainty in the time 
measurements made by the individual monitors. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_analyze_pcap_wifidelity</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/analyze/pcap/wifidelity</refname>
</refnames>
</inproceedings>
<pubdate>20080401</pubdate>
</paper>

<paper id="220">
<key>schwab-wireless</key>
<inproceedings>
<author>
<person>David Schwab</person>
<person>Rick Bunt</person>
</author>
<title>Characterising the Use of a Campus Wireless Network</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<pages>862-870</pages>
<month>--03--</month>
<year>2004</year>
<address>Hong Kong, China</address>
<publisher>IEEE</publisher>
<url>http://www.ieee-infocom.org/2004/Papers/18_1.PDF</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20040301</pubdate>
</paper>

<paper id="221">
<key>slagell-flaim</key>
<inproceedings>
<author>
<person>Adam Slagell</person>
<person>Kiran Lakkaraju</person>
<person>Katherine Luo</person>
</author>
<title>FLAIM: A Multi-level Anonymization Framework for Computer and Network Logs</title>
<booktitle>Proceeding of the 20th USENIX Large Installation System Administration Conference (LISA '06)</booktitle>
<month>--12--</month>
<year>2006</year>
<address>Washington, D.C.</address>
<url>http://laim.ncsa.uiuc.edu/downloads/slagell06.pdf</url>
<keyword>Anonymization</keyword>
<abstract>FLAIM (Framework for Log Anonymization and Information Management) addresses 
two important needs not well addressed by current log anonymizers. First, it is 
extremely modular and not tied to the specific log being anonymized. Second, it 
supports multi-level anonymization, allowing system administrators to make 
fine-grained trade-offs between information loss and privacy/security concerns. 
In this paper, we examine anonymization solutions to date and note the above 
limitations in each. We further describe how FLAIM addresses these problems, 
and we describe FLAIM's architecture and features in detail. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>tools_sanitize_generic_FLAIM</keywords>
<keywords>crawdad</keywords>
<refnames><refname>tools/sanitize/generic/FLAIM</refname>
</refnames>
</inproceedings>
<pubdate>20061201</pubdate>
</paper>

<paper id="222">
<key>song-opportunistic-routing</key>
<inproceedings>
<author>
<person>Libo Song</person>
<person>David F. Kotz</person>
</author>
<title>Evaluating opportunistic routing protocols with large realistic contact traces</title>
<booktitle>CHANTS '07: Proceedings of the second workshop on Challenged networks CHANTS</booktitle>
<year>2007</year>
<pages>35-42</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287791.1287799</doi>
<url>http://doi.acm.org/10.1145/1287791.1287799</url>
<publisher>ACM Press</publisher>
<abstract>Traditional mobile ad hoc network (MANET) routing protocols assume that 
contemporaneous end-to-end communication paths exist between data senders and 
receivers. In some mobile ad hoc networks with a sparse node population, an 
end-to-end communication path may break frequently or may not exist at any 
time. Many routing protocols have been proposed in the literature to address 
the problem, but few were evaluated in a realistic opportunistic network 
setting. We use simulation and contact traces (derived from logs in a 
production network) to evaluate and compare five existing protocols: 
direct-delivery, epidemic, random, PRoPHET, and Link-State, as well as our own 
proposed routing protocol. We show that the direct delivery and epidemic 
routing protocols suffer either low delivery ratio or high resource usage, and 
other protocols make tradeoffs between delivery ratio and resource usage. </abstract>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="223">
<key>song-predict</key>
<inproceedings>
<author>
<person>Libo Song</person>
<person>David Kotz</person>
<person>Ravi Jain</person>
<person>Xiaoning He</person>
</author>
<title>Evaluating location predictors with extensive Wi-Fi mobility data</title>
<booktitle>Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<pages>1414-1424</pages>
<month>--03--</month>
<year>2004</year>
<volume>2</volume>
<url>http://www.cs.dartmouth.edu/~dfk/papers/song:predict.pdf</url>
<keyword>mobility, location aware, location prediction, mobile computing, wireless network, dfk</keyword>
<abstract>Location is an important feature for many applications, and wireless networks 
can better serve their clients by anticipating client mobility. As a result, 
many location predictors have been proposed in the literature, though few have 
been evaluated with empirical evidence. This paper reports on the results of 
the first extensive empirical evaluation of location predictors, using a 
two-year trace of the mobility patterns of over 6,000 users on Dartmouth's 
campus-wide Wi-Fi wireless network. \par We implemented and compared the 
prediction accuracy of several location predictors drawn from two major 
families of domain-independent predictors, namely Markov-based and 
compression-based predictors. We found that low-order Markov predictors 
performed as well or better than the more complex and more space-consuming 
compression-based predictors. Predictors of both families fail to make a 
prediction when the recent context has not been previously seen. To overcome 
this drawback, we added a simple fallback feature to each predictor and found 
that it significantly enhanced its accuracy in exchange for modest effort. Thus 
the Order-2 Markov predictor with fallback was the best predictor we studied, 
obtaining a median accuracy of about 72\% for users with long trace lengths. We 
also investigated a simplification of the Markov predictors, where the 
prediction is based not on the most frequently seen context in the past, but 
the most recent, resulting in significant space and computational savings. We 
found that Markov predictors with this recency semantics can rival the accuracy 
of standard Markov predictors in some cases. Finally, we considered several 
seemingly obvious enhancements, such as smarter tie-breaking and aging of 
context information, and discovered that they had little effect on accuracy. 
The paper ends with a discussion and suggestions for further work. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20040301</pubdate>
</paper>

<paper id="224">
<key>song-predict-poster</key>
<article>
<author>
<person>Libo Song</person>
<person>David Kotz</person>
<person>Ravi Jain</person>
<person>Xiaoning He</person>
</author>
<title>MobiCom Poster: Evaluating location predictors with extensive Wi-Fi mobility data</title>
<journal>ACM SIGMOBILE Mobile Computing and Communication Review</journal>
<year>2003</year>
<month>--10--</month>
<volume>7</volume>
<number>4</number>
<pages>64-65</pages>
<url>http://doi.acm.org/10.1145/965732.965747</url>
<keyword>mobility, location aware, location prediction, mobile computing, wireless network, dfk</keyword>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</article>
<pubdate>20031001</pubdate>
</paper>

<paper id="225">
<key>song-predict-tr</key>
<techreport>
<author>
<person>Libo Song</person>
<person>David Kotz</person>
<person>Ravi Jain</person>
<person>Xiaoning He</person>
</author>
<title>Evaluating location predictors with extensive Wi-Fi mobility data</title>
<year>2004</year>
<month>--02--</month>
<number>TR2004-491</number>
<institution>Dept. of Computer Science, Dartmouth College</institution>
<url>http://www.cs.dartmouth.edu/reports/abstracts/TR2004-491/</url>
<urlpdf>http://www.cs.dartmouth.edu/ dfk/papers/song:predict-tr.pdf</urlpdf>
<keyword>mobility, location aware, location prediction, mobile computing, wireless network, dfk</keyword>
<abstract>Location is an important feature for many applications, and wireless networks 
can better serve their clients by anticipating client mobility. As a result, 
many location predictors have been proposed in the literature, though few have 
been evaluated with empirical evidence. This paper reports on the results of 
the first extensive empirical evaluation of location predictors, using a 
two-year trace of the mobility patterns of over 6,000 users on Dartmouth's 
campus-wide Wi-Fi wireless network. We implemented and compared the prediction 
accuracy of several location predictors drawn from four major families of 
domain-independent predictors, namely Markov-based, compression-based, PPM, and 
SPM predictors. We found that low-order Markov predictors performed as well or 
better than the more complex and more space-consuming compression-based 
predictors. Predictors of both families fail to make a prediction when the 
recent context has not been previously seen. To overcome this drawback, we 
added a simple fallback feature to each predictor and found that it 
significantly enhanced its accuracy in exchange for modest effort. Thus the 
Order-2 Markov predictor with fallback was the best predictor we studied, 
obtaining a median accuracy of about 72\% for users with long trace lengths. We 
also investigated a simplification of the Markov predictors, where the 
prediction is based not on the most frequently seen context in the past, but 
the most recent, resulting in significant space and computational savings. We 
found that Markov predictors with this recency semantics can rival the accuracy 
of standard Markov predictors in some cases. Finally, we considered several 
seemingly obvious enhancements, such as smarter tie-breaking and aging of 
context information, and discovered that they had little effect on accuracy. 
The paper ends with a discussion and suggestions for further work. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</techreport>
<pubdate>20040201</pubdate>
</paper>

<paper id="226">
<key>song-reserv</key>
<inproceedings>
<author>
<person>Libo Song</person>
<person>Udayan Deshpande</person>
<person>Ulas C. Kozat</person>
<person>David Kotz</person>
<person>Ravi Jain</person>
</author>
<title>Predictability of WLAN Mobility and its Effects on Bandwidth Provisioning</title>
<booktitle>Proceedings of the 25th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<year>2006</year>
<month>--04--</month>
<url>http://www.cs.dartmouth.edu/~dfk/papers/song:reserv.pdf</url>
<address>Barcelona, Spain</address>
<keyword>mobile computing, location prediction, mobility prediction, VoIP, QoS, bandwidth reservation, channel allocation, dfk</keyword>
<abstract>Wireless local area networks (WLANs) are emerging as a popular technology for 
access to the Internet and enterprise networks. In the long term, the success 
of WLANs depends on services that support mobile network clients. Mobility 
prediction holds a key value that is widely acknowledged in the literature. 
\par Although other researchers have explored mobility prediction in 
hypothetical scenarios, evaluating their predictors analytically or with 
synthetic data, few studies have been able to evaluate their predictors with 
real user mobility data. As a first step towards filling this fundamental gap, 
we work with a large data set collected from the Dartmouth College campus-wide 
wireless network that hosts more than 500 access points and 6,000 users. 
Extending our earlier work that focuses on predicting the next-visited access 
point (i.e., location), in this work we explore the predictability of the time 
of user mobility. Indeed, our contributions are two-fold. First, we evaluate a 
series of predictors that reflect possible dependencies across time and space 
while benefiting from either individual or group mobility behaviors. Second, as 
a case study we examine voice applications and the use of handoff prediction 
for advance bandwidth reservation. Using application-specific performance 
metrics such as call drop and call block rates, we provide a complete picture 
on the gains of prediction. \par Our results indicate that it is difficult to 
predict handoff time accurately, when applied to real campus WLAN data. 
However, the findings of our case study also suggest that the application 
performance can be improved significantly even with predictors that are only 
moderately accurate. The gains depend on the applications' ability to use 
predictions and tolerate inaccurate predictions. In the case study, we combine 
the real mobility data with synthesized traffic data. The results show that 
intelligent prediction can lead to significant reductions in the rate at which 
active calls are dropped due to handoffs with marginal increments in the rate 
at which new calls are blocked. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="227">
<key>song-reserv-mc2r</key>
<article>
<author>
<person>Libo Song</person>
<person>Udayan Deshpande</person>
<person>Ula\cs C. Kozat</person>
<person>David Kotz</person>
<person>Ravi Jain</person>
</author>
<title>MobiCom Poster Abstract: Bandwidth Reservation using WLAN Handoff Prediction</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<journal>ACM SIGMOBILE Mobile Computing and Communication Review</journal>
<year>2006</year>
<note>Accepted for publication</note>
<url>http://www.cs.dartmouth.edu/~dfk/papers/song:reserv-mc2r.pdf</url>
<keyword>mobile computing, location prediction, mobility prediction, VoIP, QoS, bandwidth reservation, channel allocation, dfk</keyword>
<category>crawdad</category>
</article>
<pubdate>20060001</pubdate>
</paper>

<paper id="228">
<key>song-reserv-poster</key>
<misc>
<author>
<person>Libo Song</person>
<person>Udayan Deshpande</person>
<person>Ula\cs C. Kozat</person>
<person>David Kotz</person>
<person>Ravi Jain</person>
</author>
<title>Bandwidth Reservation using WLAN Handoff Prediction</title>
<year>2005</year>
<month>--08--</month>
<category>crawdad</category>
<howpublished>Poster presentation at MobiCom 2005</howpublished>
<url>http://www.cs.dartmouth.edu/~dfk/papers/song:reserv-poster.pdf</url>
<keyword>mobile computing, location prediction, mobility prediction, VoIP, QoS, bandwidth reservation, channel allocation, dfk</keyword>
<abstract>Many network services may be improved or enabled by successful predictions on 
users' future mobility. The success of predictions depend on how much accuracy 
can be achieved on real data and on the sensitivity of particular application 
to this achievable accuracy. We investigate these issues for the case of 
advanced bandwidth reservation using real WLAN traces collected at Dartmouth 
College Campus. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</misc>
<pubdate>20050801</pubdate>
</paper>

<paper id="229">
<key>song-thesis</key>
<techreport>
<author><person>Libo Song</person>
</author>
<title>Evaluating Mobility Predictors in Wireless Networks for Improving Handoff and Opportunistic Routing</title>
<institution>Dartmouth College, Computer Science</institution>
<address>Hanover, NH</address>
<number>TR2008-611</number>
<year>2008</year>
<month>--01--</month>
<url>http://www.cs.dartmouth.edu/reports/TR2008-611.pdf</url>
<abstract>We evaluate mobility predictors in wireless networks. Handoff prediction in 
wireless networks has long been considered as a mechanism to improve the 
quality of service provided to mobile wireless users. Most prior studies, 
however, were based on theoretical analysis, simulation with synthetic mobility 
models, or small wireless network traces. We study the effect of mobility 
prediction for a large realistic wireless situation. We tackle the problem by 
using traces collected from a large production wireless network to evaluate 
several major families of handoff-location prediction techniques, a set of 
handoff-time predictors, and a predictor that jointly predicts handoff location 
and time. We also propose a fallback mechanism, which uses a lower-order 
predictor whenever a higher-order predictor fails to predict. We found that 
low-order Markov predictors, with our proposed fallback mechanisms, performed 
as well or better than the more complex and more space-consuming 
compression-based handoff-location predictors. Although our handoff-time 
predictor had modest prediction accuracy, in the context of mobile voice 
applications we found that bandwidth reservation strategies can benefit from 
the combined location and time handoff predictor, significantly reducing the 
call-drop rate without significantly increasing the call-block rate. We also 
developed a prediction-based routing protocol for mobile opportunistic 
networks. We evaluated and compared our protocol's performance to five existing 
routing protocols, using simulations driven by real mobility traces. We found 
that the basic routing protocols are not practical for large-scale 
opportunistic networks. Prediction-based routing protocols trade off the 
message delivery ratio against resource usage and performed well and comparable 
to each other. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</techreport>
<pubdate>20080101</pubdate>
</paper>

<paper id="230">
<key>souryal-multihop</key>
<inproceedings>
<author>
<person>Michael R. Souryal</person>
<person>Johannes Geissbuehler</person>
<person>Leonard E. Miller</person>
<person>Nader Moayeri</person>
</author>
<title>Real-time deployment of multihop relays for range extension</title>
<booktitle>MobiSys '07: Proceedings of the 5th international conference on Mobile systems, applications and services</booktitle>
<year>2007</year>
<month>--06--</month>
<pages>85-98</pages>
<address>San Juan, Puerto Rico</address>
<doi>http://doi.acm.org/10.1145/1247660.1247673</doi>
<url>http://doi.acm.org/10.1145/1247660.1247673</url>
<publisher>ACM Press</publisher>
<keyword>Deployment, multihop wireless networks, first responders, breadcrumbs, sensors, RFID</keyword>
<abstract>When the range of single-hop wireless communication is limited by distance or 
harsh radio propagation conditions, relays can be used to extend the 
communication range through multihop relaying. This paper targets the need in 
certain scenarios for rapid deployment of these relays when little or nothing 
is known in advance about a given environment and its propagation 
characteristics. Applications include first responders entering a large 
building during an emergency, search and rescue robots maneuvering a disaster 
sight, and coal miners working underground. The common element motivating this 
work is the need to maintain communications in an environment where single-hop 
communication is typically inadequate. This paper investigates the feasibility 
of the automated deployment of a multihop network. A deployment procedure is 
proposed that employs real-time link measurements and takes into account the 
physical layer characteristics of a mobile multipath fading environment and the 
radio in use. A prototype system is implemented based on 900 MHz TinyOS motes 
supporting low-speed data applications including text messaging, sensor data 
and Radio Frequency Identification (RFID)-assisted localization. Results of 
deployments in a hi-rise office building are presented. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>nist_multihop</keywords>
<keywords>crawdad</keywords>
<refnames><refname>nist/multihop</refname>
</refnames>
</inproceedings>
<pubdate>20070601</pubdate>
</paper>

<paper id="231">
<key>sridhara-gain</key>
<inproceedings>
<author>
<person>Vinay Sridhara</person>
<person>Hwee-Chul Shin</person>
<person>Stephan Bohacek</person>
</author>
<title>Observations and Models of Time-Varying Channel Gain in Crowded Areas</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/03-04.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="232">
<key>srinivasan-contact</key>
<inproceedings>
<author>
<person>Vikram Srinivasan</person>
<person>Mehul Motani</person>
<person>Wei Tsang Ooi</person>
</author>
<title>Analysis and Implications of Student Contact Patterns Derived from Campus Schedules</title>
<booktitle>Proceedings of the Twelfth Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<month>--09--</month>
<year>2006</year>
<address>Los Angeles, CA</address>
<url>http://www.comp.nus.edu.sg/~ooiwt/papers/contact-mobicom06-final.pdf</url>
<category>crawdad</category>
<abstract>Characterizing mobility or contact patterns in a campus environment is of 
interest for a variety of reasons. Existing studies of these patterns can be 
classified into two basic approaches - model based and measurement based. The 
model based approach involves constructing a mathematical model to generate 
movement patterns while the measurement based approachmeasures locations and 
proximity of wireless devices to infer mobility patterns. In this paper, we 
take a completely different approach. First we obtain the class schedules and 
class rosters from a university-wide Intranet learning portal, and use this 
information to infer contacts made between students. The value of our approach 
is in the population size involved in the study, where contact patterns among 
22341 students are analyzed. This paper presents the characteristics of these 
contact patterns, and explores how these patterns affect three scenarios. We 
first look at the characteristics from the DTN perspective, where we study 
inter-contact time and time distance between pairs of students. Next, we 
present how these characteristics impact the spread of mobile computer viruses, 
and show that viruses can spread to virtually the entire student population 
within a day. Finally, we consider aggregation of information from a large 
number of mobile, distributed sources, and demonstrate that the contact 
patterns can be exploited to design efficient aggregation algorithms, in which 
only a small number of nodes (less than 0.5%) is needed to aggregate a large 
fraction (over 90%) of the data. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>nus_contact</keywords>
<keywords>crawdad</keywords>
<refnames><refname>nus/contact</refname>
</refnames>
</inproceedings>
<pubdate>20060901</pubdate>
</paper>

<paper id="233">
<key>srivastava-maniac</key>
<inproceedings>
<author>
<person>V. Srivastava</person>
<person>A. Hilal</person>
<person>M. S. Thompson</person>
<person>J. N. Chattha</person>
<person>A. B. MacKenzie</person>
<person>L. A. DaSilva</person>
</author>
<title>Characterizing Mobile Ad Hoc Networks - The MANIAC Challenge Experiment</title>
<year>2008</year>
<booktitle>Proceedings of the Third ACM International Workshop on Wireless Network Testbeds, Experimental evaluation and CHaracterization (WiNTECH)</booktitle>
<address>San Francisco, CA</address>
<month>--09--</month>
<url>http://www.maniacchallenge.org/srivastava.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>vt_maniac</keywords>
<keywords>crawdad</keywords>
<refnames><refname>vt/maniac</refname>
</refnames>
<abstract>This paper reports data collected during the first Mobile Ad-hoc Network 
Interoperability And Cooperation (MANIAC) Challenge, a multi-institution 
competition that allows us to study issues of interoperability and cooperation 
in mobile ad hoc networks (MANETs). We characterize network topology and 
routing. The former includes network connectivity and diameter, node degree 
distribution, clustering, and frequency of topology changes. The latter 
includes route length distribution, route asymmetry, frequency of route 
changes, and packet delivery ratio. Results show a high degree of topology and 
route changes, even when mobility is low, and a prevalence of asymmetric 
routes, both of which contradict assumptions commonly made in MANET simulation 
studies. Our data sets will be made publicly available for use by other 
researchers. </abstract>
</inproceedings>
<pubdate>20080901</pubdate>
</paper>

<paper id="234">
<key>strayer-botnet-book</key>
<inproceedings>
<author>
<person>Strayer, W. T.</person>
<person>Lapsley, D.</person>
<person>Walsh, R.</person>
<person>Livadas, C.</person>
</author>
<title>Botnet Detection Based on Network Behavior</title>
<booktitle>Botnet Detection: Countering the Largest Security Threat</booktitle>
<editor>Wenke Lee and Cliff Wang and David Dagon</editor>
<publisher>Springer-Verlag</publisher>
<year>2007</year>
<url>http://dx.doi.org/10.1007/978-0-387-68768-1_1</url>
<category>wireless-meas, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="235">
<key>strayer-botnets</key>
<inproceedings>
<author>
<person>Strayer, W. T.</person>
<person>Walsh, R.</person>
<person>Livadas, C.</person>
<person>Lapsley, D.</person>
</author>
<title>Detecting Botnets with Tight Command and Control</title>
<booktitle>Proceedings of the 31st IEEE Conference on Local Computer Networks</booktitle>
<year>2006</year>
<pages>195-202</pages>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
<url>http://www.ir.bbn.com/documents/articles/botnet-lcn-06.pdf</url>
<abstract>Systems are attempting to detect botnets by examining traffic content for IRC 
commands or by setting up honeynets. Our approach for detecting botnets is to 
examine flow characteristics such as bandwidth, duration, and packet timing 
looking for evidence of botnet command and control activity. We have 
constructed an architecture that first eliminates traffic that is unlikely to 
be a part of a botnet, classifies the remaining traffic into a group that is 
likely to be part of a botnet, then correlates the likely traffic to find 
common communications patterns that would suggest the activity of a botnet. Our 
results show that botnet evidence can be extracted from a traffic trace 
containing almost 9 million flows. </abstract>
<category>wireless-meas, crawdad</category>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="236">
<key>su-bluetooth</key>
<inproceedings>
<author>
<person>J. Su</person>
<person>K.K. Chan</person>
<person>A.G. Miklas</person>
<person>K. Po</person>
<person>A. Akhavan</person>
<person>S. Saroiu</person>
<person>E.D. Lara</person>
<person>A. Goel</person>
</author>
<title>A Preliminary Investigation of Worm Infections in a Bluetooth Environment</title>
<booktitle>Proceedings of the ACM Workshop on Rapid Malcode (WORM)</booktitle>
<month>--11--</month>
<year>2006</year>
<address>Alexandria, VA, USA</address>
<url>http://www.cs.toronto.edu/~stefan/publications/worm/2006/bt.pdf</url>
<abstract>Over the past year, there have been several reports of malicious code 
exploiting vulnerabilities in the Bluetooth protocol. While the research 
community has started to investigate a diverse set of Bluetooth security 
issues, little is known about the feasibility and the propagation dynamics of a 
worm in a Bluetooth environment. This paper is an initial attempt to remedy 
this situation. We start by showing that the Bluetooth protocol design and 
implementation is large and complex. We gather traces and we use controlled 
experiments to investigate whether a large-scale Bluetooth worm outbreak is 
viable today. Our data shows that starting a Bluetooth worm infection is easy, 
once a vulnerability is discovered. Finally, we use trace-drive simulations to 
examine the propagation dynamics of Bluetooth worms. We find that Bluetooth 
worms can infect a large population of vulnerable devices relatively quickly, 
in just a few days. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>toronto_bluetooth</keywords>
<keywords>crawdad</keywords>
<refnames><refname>toronto/bluetooth</refname>
</refnames>
</inproceedings>
<pubdate>20061101</pubdate>
</paper>

<paper id="237">
<key>subramanian-multi-channel</key>
<inproceedings>
<author>
<person>Anand Prabhu Subramanian</person>
<person>Jing Cao</person>
<person>Chul Sung</person>
<person>Samir R. Das</person>
</author>
<title>Understanding Channel and Interface Heterogeneity in Multi-channel Multi-radio Wireless Mesh Networks</title>
<booktitle>Tenth Passive and Active Measurement conference (PAM)</booktitle>
<year>2009</year>
<month>--04--</month>
<address>Seoul, South Korea</address>
<url>http://www.wings.cs.sunysb.edu/~anandps/pub/anand-pam09.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>sunysb_multi_channel</keywords>
<keywords>crawdad</keywords>
<refnames><refname>sunysb/multi_channel</refname>
</refnames>
</inproceedings>
<pubdate>20090401</pubdate>
</paper>

<paper id="238">
<key>sun-experimental</key>
<inproceedings>
<author>
<person>Yuan Sun</person>
<person>Irfan Sheriff</person>
<person>Elizabeth M. Belding-Royer</person>
<person>Kevin C. Almeroth</person>
</author>
<title>An Experimental Study of Multimedia Traffic Performance in Mesh Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>25-30</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://portal.acm.org/citation.cfm?id=1072430.1072435</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="239">
<key>sun-measurement</key>
<inproceedings>
<author>
<person>Tony Sun</person>
<person>Guang Yang</person>
<person>Ling-Jyh Chen</person>
<person>M.Y. Sanadidi</person>
<person>Mario Gerla</person>
</author>
<title>A Measurement Study of Path Capacity in 802.11b-based Wireless Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>31-37</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://portal.acm.org/citation.cfm?id=1072436</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="240">
<key>tan-fairness</key>
<inproceedings>
<author>
<person>Godfrey Tan</person>
<person>John Guttag</person>
</author>
<title>Time-based Fairness Improves Performance in Multi-rate WLANs</title>
<booktitle>Proceedings of the 2004 USENIX Technical Conference</booktitle>
<month>--06--</month>
<year>2004</year>
<publisher>USENIX Association</publisher>
<url>http://nms.lcs.mit.edu/papers/tbr_usenix04.pdf</url>
<keyword>wireless network, measurement</keyword>
<abstract>The performance seen by individual clients on a wireless local area network 
(WLAN) is heavily influenced by the manner in which wireless channel capacity 
is allocated. The popular MAC protocol DCF (Distributed Coordination Function) 
used in 802.11 networks provides equal long-term transmission opportunities to 
competing nodes when all nodes experience similar channel conditions. When 
similar-sized packets are also used, DCF leads to equal achieved throughputs 
(throughput based fairness) among contending nodes. \par Because of varying 
indoor channel conditions, the 802.11 standard supports multiple data 
transmission rates to exploit the trade-off between data rate and bit error 
rate. This leads to considerable rate diversity, particularly when the network 
is congested. Under such conditions, throughput-based fairness can lead to 
drastically reduced aggregate throughput. \par In this paper, we argue the 
advantages of time-based fairness, in which each competing node receives an 
equal share of the wireless channel occupancy time. We demonstrate that this 
notion of fairness can lead to significant improvements in aggregate 
performance while still guaranteeing that no node receives worse channel access 
than it would in a single-rate WLAN. We also describe our algorithm, TBR 
(Time-based Regulator), which runs on the AP and works with any MAC protocol to 
provide time-based fairness by regulating packets. Through experiments, we show 
that our practical and backward compatible implementation of TBR in conjunction 
with an existing implementation of DCF achieves time-based fairness. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20040601</pubdate>
</paper>

<paper id="241">
<key>tang-wavelan</key>
<inproceedings>
<author>
<person>Diane Tang</person>
<person>Mary Baker</person>
</author>
<title>Analysis of a Local-Area Wireless Network</title>
<booktitle>Proceedings of the Sixth Annual International Conference on Mobile Computing and Networking (MobiCom)</booktitle>
<pages>1-10</pages>
<month>--08--</month>
<year>2000</year>
<address>Boston, MA</address>
<publisher>ACM Press</publisher>
<url>http://www.acm.org/pubs/citations/proceedings/comm/345910/p1-tang/</url>
<keyword>mobile computing, wireless network</keyword>
<abstract>To understand better how users take advantage of wireless networks, we examine 
a twelve-week trace of a building-wide local-area wireless network. We analyze 
the network for overall user behavior (when and how intensively people use the 
network and how much they move around), overall network traffic and load 
characteristics (observed throughput and symmetry of incoming and outgoing 
traffic), and traffic characteristics from a user point of view (observed mix 
of applications and number of hosts connected to by users). Amongst other 
results, we find that users are divided into distinct location-based 
sub-communities, each with its own movement, activity, and usage 
characteristics. Most users exploit the network for web-surfing, 
session-oriented activities and chat-oriented activities. The high number of 
chat-oriented activities shows that many users take advantage of the mobile 
network for for synchronous communication with others. In addition to these 
user-specific results, we find that peak throughput is usually caused by a 
single user and application. Also, while incoming traffic dominates outgoing 
traffic overall, the opposite tends to be true during periods of peak 
throughput, implying that significant asymmetry in network capacity could be 
undesirable for our users. While these results are only valid for this 
local-area wireless network and user community, we believe that similar 
environments may exhibit similar behavior and trends. We hope that our 
observations will contribute to a growing understanding of mobile user 
behavior. </abstract>
<category>wireless-meas, crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>stanford_gates</keywords>
<keywords>crawdad</keywords>
<refnames><refname>stanford/gates</refname>
</refnames>
</inproceedings>
<pubdate>20000801</pubdate>
</paper>

<paper id="242">
<key>thelen-radio</key>
<inproceedings>
<author>
<person>John Thelen</person>
<person>Daan Goense</person>
<person>Koen Langendoen</person>
</author>
<title>Radio Wave Propagation in Potato Fields</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Thelen.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="243">
<key>thompson-multihoming</key>
<inproceedings>
<author>
<person>Nathanael Thompson</person>
<person>Guanghui He</person>
<person>Haiyun Luo</person>
</author>
<title>Flow Scheduling for End-host Multihoming</title>
<booktitle>Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM)</booktitle>
<month>--04--</month>
<year>2006</year>
<address>Barcelona, Spain</address>
<url>http://swing.cs.uiuc.edu/papers/INFOCOM06PERM.pdf</url>
<abstract>Fueled by the competing DSL and Cable technologies, residential broadband 
access has seen a significant spread in availability to the point that many 
users have a choice from several ISPs. At the same time, 802.11 networks have 
spread rapidly in the residential area, and it is common for neighbors to be 
able to access each other's wireless routers. End-users can leverage this 
diversity to improve their Internet connectivity at no additional cost by 
pooling all available Internet connections, both their own and their neighbors' 
via wireless. In this paper we present our design and evaluation of flow 
scheduling algorithms in PERM, a framework for practical end-host multihoming. 
PERM scheduler employs automated on-line analysis of the endusers' networking 
behaviors, and exploits the recognized patterns to achieve high-performance 
scheduling at flow level. We verify our models of end-user's network traffic 
with large residential TCP traces. Based on these models we propose algorithms 
for scalable pre-probing and hybrid flow scheduling. Intensive experiments in 
our prototype testbed show that PERM scheduler reduces the latency by up to 50% 
for light-volume flows, and reduces the mean transmission time of heavy-volume 
flows by nearly 28% and 62% compared with a single Cable or DSL connection 
respectively. The PERM scheduler also out-performs algorithms for enterprise 
multihoming by up to 15% and 27% in mean transmission time for light- and 
heavy-volume flows respectively. </abstract>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="244">
<key>tournoux-rollernet</key>
<inproceedings>
<author>
<person>Pierre Ugo Tournoux</person>
<person>J&#233;r&#233;mie Leguay</person>
<person>Farid Benbadis</person>
<person>Vania Conan</person>
<person>Marcelo Dias de Amorim</person>
<person>John Whitbeck</person>
</author>
<title>The Accordion Phenomenon: Analysis, Characterization, and Impact on DTN Routing</title>
<booktitle>Proceedings of the 28rd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM)</booktitle>
<month>--04--</month>
<year>2009</year>
<address>Rio de Janeiro, Brazil</address>
<publisher>IEEE</publisher>
<url>http://jeremie.leguay.free.fr/lip6/files/RollerNet-Infocom09.pdf</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>upmc_rollernet</keywords>
<keywords>crawdad</keywords>
<refnames><refname>upmc/rollernet</refname>
</refnames>
</inproceedings>
<pubdate>20090401</pubdate>
</paper>

<paper id="245">
<key>tuduce-mobility</key>
<inproceedings>
<author>
<person>Cristian Tuduce</person>
<person>Thomas Gross</person>
</author>
<title>A Mobility Model Based on WLAN Traces and its Validation</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the 24th IEEE International Conference on Computer Communications (INFOCOM)</booktitle>
<pages>664-674</pages>
<month>--03--</month>
<year>2005</year>
<address>Miami, FL, USA</address>
<url>http://www.lst.inf.ethz.ch/research/publications/publications/INFOCOM_2005/INFOCOM_2005.pdf</url>
<abstract>The simulation of mobile networks calls for a mobility model to generate the 
trajectories of the mobile users (or nodes). It has been shown that the 
mobility model has a major influence on the behavior of the system. Therefore, 
using a realistic mobility model is important if we want to increase the 
confidence that simulations of mobile systems are meaningful in realistic 
settings. In this paper we present an executable mobility model that uses 
real-life mobility characteristics to generate mobility scenarios that can be 
used for network simulations. We present a structured framework for extracting 
the mobility characteristics from a WLAN trace, for processing the mobility 
characteristics to determine a parameter set for the mobility model, and for 
using a parameter set to generate mobility scenarios for simulations. To derive 
the parameters of the mobility model, we measure the mobility characteristics 
of users of a campus wireless network. Therefore, we call this model the WLAN 
mobility model. Mobility analysis confirms properties observed by other 
research groups. The validation shows that the WLAN model maps the real-world 
mobility characteristics to the abstract world of network simulators with a 
very small error. For users that do not have the possibility to capture a WLAN 
trace, we explore the value space of the WLAN model parameters and show how 
different parameters sets influence the mobility of the simulated nodes. </abstract>
<category>wireless-meas</category>
<doi>10.1109/INFCOM.2005.1497932</doi>
</inproceedings>
<pubdate>20050301</pubdate>
</paper>

<paper id="246">
<key>vaidya-illinois</key>
<inproceedings>
<author>
<person>Nitin Vaidya</person>
<person>Jennifer Bernhard</person>
<person>Venugopal Veeravalli</person>
<person>P. R. Kumar</person>
<person>Ravi Iyer</person>
</author>
<title>Illinois Wireless Wind Tunnel: A Testbed for Experimental Evaluation of Wireless Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-VaiBer.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="247">
<key>vu-3r</key>
<article>
<author>
<person>Long Vu</person>
<person>Quang Do</person>
<person>Klara Nahrstedt</person>
</author>
<title>3R: Fine-grained encounter-based routing in Delay Tolerant Networks</title>
<journal>2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)</journal>
<year>2011</year>
<pages>1-6</pages>
<publisher>IEEE Computer Society</publisher>
<address>Lucca</address>
<url>http://monet.web.cs.illinois.edu/publications/papers/Jyotish-percom2011-camera-7.pdf</url>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>uiuc_uim</keywords>
<category>wireless-meas</category>
<refnames><refname>uiuc/uim</refname>
</refnames>
</article>
<pubdate>20110001</pubdate>
</paper>

<paper id="248">
<key>vu-joint</key>
<inproceedings>
<author>
<person>Vu, Long</person>
<person>Nahrstedt, Klara</person>
<person>Retika, Samuel</person>
<person>Gupta, Indranil</person>
</author>
<title>Joint Bluetooth/Wifi scanning framework for characterizing and leveraging people movement in university campus</title>
<booktitle>Proceedings of the 13th ACM international conference on modeling, analysis, and simulation of wireless and mobile systems</booktitle>
<series>MSWIM '10</series>
<year>2010</year>
<pages>257-265</pages>
<url>http://dprg.cs.uiuc.edu/docs/mswim2010/mswim2010.pdf</url>
<publisher>ACM</publisher>
<address>New York, NY, USA</address>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>uiuc_uim</keywords>
<category>wireless-meas</category>
<refnames><refname>uiuc/uim</refname>
</refnames>
</inproceedings>
<pubdate>20100001</pubdate>
</paper>

<paper id="249">
<key>vu-jyotish</key>
<article>
<author>
<person>Long Vu</person>
<person>Quang Do</person>
<person>Klara Nahrstedt</person>
</author>
<title>Jyotish: A novel framework for constructing predictive model of people movement from joint Wifi/Bluetooth trace</title>
<journal>IEEE International Conference on Pervasive Computing and Communications</journal>
<url>http://monet.web.cs.illinois.edu/publications/papers/Jyotish-percom2011-camera-7.pdf</url>
<volume>0</volume>
<year>2011</year>
<pages>54-62</pages>
<publisher>IEEE Computer Society</publisher>
<address>Los Alamitos, CA, USA</address>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>uiuc_uim</keywords>
<category>wireless-meas</category>
<refnames><refname>uiuc/uim</refname>
</refnames>
</article>
<pubdate>20110001</pubdate>
</paper>

<paper id="250">
<key>vu-jyotish2</key>
<article>
<author>
<person>Long Vu</person>
<person>Quang Do</person>
<person>Klara Nahrstedt</person>
</author>
<title>Jyotish: Constructive approach for context predictions of people movement from joint Wifi/Bluetooth trace</title>
<journal>The Ninth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2011)</journal>
<volume>7</volume>
<number>6</number>
<pages>690-704</pages>
<year>2011</year>
<keywords>wireless</keywords>
<keywords>measurement</keywords>
<keywords>uiuc_uim</keywords>
<category>wireless-meas</category>
<refnames><refname>uiuc/uim</refname>
</refnames>
</article>
<pubdate>20110001</pubdate>
</paper>

<paper id="251">
<key>walsh-mobility-model-poster</key>
<misc>
<author>
<person>Chris Walsh</person>
<person>Arta Doci</person>
<person>Tracy Camp</person>
</author>
<title>A Call to Arms: It's time for REAL Mobility Models</title>
<year>2007</year>
<month>--09--</month>
<category>crawdad</category>
<howpublished>Poster presentation at MobiCom 2007</howpublished>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</misc>
<pubdate>20070901</pubdate>
</paper>

<paper id="252">
<key>wang-adaptive</key>
<inproceedings>
<author>
<person>Wei Wang</person>
<person>Vikram Srinivasan</person>
<person>Mehul Motani</person>
</author>
<title>Adaptive contact probing mechanisms for delay tolerant applications</title>
<booktitle>MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking</booktitle>
<year>2007</year>
<pages>230-241</pages>
<address>Montreal, Quebec, Canada</address>
<doi>http://doi.acm.org/10.1145/1287853.1287882</doi>
<url>http://doi.acm.org/10.1145/1287853.1287882</url>
<publisher>ACM Press</publisher>
<abstract>In many delay tolerant applications, information is opportunistically exchanged 
between mobile devices who encounter each other. In order to effect such 
information exchange, mobile devices must have knowledge of other devices in 
their vicinity. We consider scenarios in which there is no infrastructure and 
devices must probe their environment to discover other devices. This can be an 
extremely energy consuming process and highlights the need for energy conscious 
contact probing mechanisms. If devices probe very infrequently, they might miss 
many of their contacts. On the other hand, frequent contact probing might be 
energy inefficient. In this paper, we investigate the trade-off between the 
probability of missing a contact and the contact probing frequency. First, via 
theoretical analysis, we characterize the trade-off between the probability of 
a missed contact and the contact probing interval for stationary processes. 
Next, for time varying contact arrival rates, we provide an optimization 
framework to compute the optimal contact probing interval as a function of the 
arrival rate. We characterize real world contact patterns via Bluetooth phone 
contact logging experiments and show that the contact arrival process is 
self-similar. We design STAR, a contact probing algorithm which adapts to the 
contact arrival process. Via trace driven simulations on our experimental data, 
we show that STAR consumes three times less energy when compared to a constant 
contact probing interval scheme. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>nus_bluetooth</keywords>
<keywords>crawdad</keywords>
<refnames><refname>nus/bluetooth</refname>
</refnames>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="253">
<key>wang-measurement</key>
<inproceedings>
<author>
<person>Wang, Xiaofei</person>
<person>Kim, Hyunchul</person>
<person>Vasilakos, Athanasios V.</person>
<person>Kwon, Ted</person>
<person>Choi, Yanghee</person>
<person>Choi, Sunghyun</person>
<person>Jang, Hanyoung</person>
</author>
<title>Measurement and analysis of World of Warcraft in mobile WiMAX networks</title>
<booktitle>Proceedings of the 8th Annual Workshop on Network and Systems Support for Games (NetGames)</booktitle>
<pages>1-6</pages>
<year>2009</year>
<month>--11--</month>
<url>http://mmlab.snu.ac.kr/~dobby/assets/2009_NETGAMES.pdf</url>
<publisher>IEEE</publisher>
<abstract>Online games have been played mainly over wired networks due to high speed 
links and capable desktop computers. The advances in mobile devices and ever 
increasing wireless link bandwidth motivate us to study whether players can 
enjoy online gaming over broadband wireless networks such as mobile WiMAX 
networks. In this paper we carry out the World of Warcraft (WoW) measurements 
via the mobile WiMAX networks and analysis the performance. We focus on two 
aspects: (1) application level packet dynamics such as RTT and jitter; (2) 
WiMAX link level statistics such as wireless link quality and handovers. We 
measure various scenarios for comprehensive analysis of WoW traffic and WiMAX 
link-layer characteristics. Finally we discuss how to improve the service 
quality of WiMAX online gaming. </abstract>
<keywords>measurement</keywords>
<keywords>analysis</keywords>
<keywords>online game</keywords>
<keywords>WiMAX</keywords>
<keywords>crawdad</keywords>
<keywords>snu_wow_via_wimax</keywords>
<category>wireless-meas,crawdad</category>
<refnames><refname>snu/wow_via_wimax</refname>
</refnames>
</inproceedings>
<pubdate>20091101</pubdate>
</paper>

<paper id="254">
<key>wang-opportunistic</key>
<inproceedings>
<author>
<person>Yong Wang</person>
<person>Sushant Jain</person>
<person>Margaret Martonosi</person>
<person>Kevin Fall</person>
</author>
<title>Erasure Coding Based Routing for Opportunistic Networks</title>
<booktitle>Proceeding of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<publisher>ACM Press</publisher>
<url>http://portal.acm.org/citation.cfm?id=1080140</url>
<keyword>Routing, Delay Tolerant Network, Erasure Coding</keyword>
<abstract>Routing in Delay Tolerant Networks (DTN) with unpredictable node mobility is a 
challenging problem because disconnections are prevalent and lack of knowledge 
about network dynamics hinders good decision making. Current approaches are 
primarily based on redundant transmissions. They have either high overhead due 
to excessive transmissions or long delays due to the possibility of making 
wrong choices when forwarding a few redundant copies. In this paper, we propose 
a novel forwarding algorithm based on the idea of erasure codes. Erasure coding 
allows use of a large number of relays while maintaining a constant overhead, 
which results in fewer cases of long delays. We use simulation to compare the 
routing performance of using erasure codes in DTN with four other categories of 
forwarding algorithms proposed in the literature. Our simulations are based on 
a real-world mobility trace collected in a large outdoor wild-life environment. 
The results show that the erasure-coding based algorithm provides the best 
worst-case delay performance with a fixed amount of overhead. We also present a 
simple analytical model to capture the delay characteristics of erasure-coding 
based forwarding, which provides insights on the potential of our approach. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>princeton_zebranet</keywords>
<keywords>crawdad</keywords>
<refnames><refname>princeton/zebranet</refname>
</refnames>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="255">
<key>wang-situation-aware</key>
<inproceedings>
<author>
<person>Yong Wang</person>
<person>Margaret Martonosi</person>
<person>Li-Shiuan Peh</person>
</author>
<title>Situation-Aware Caching Strategies in Highly Varying Mobile Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>MASCOTS '06: Proceedings of the 14th IEEE International Symposium on Modeling, Analysis, and Simulation</booktitle>
<year>2006</year>
<pages>265-274</pages>
<url>http://dx.doi.org/10.1109/MASCOTS.2006.45</url>
<doi>10.1109/MASCOTS.2006.45</doi>
<publisher>IEEE Computer Society</publisher>
<address>Washington, DC, USA</address>
<category>wireless-meas, crawdad</category>
</inproceedings>
<pubdate>20060001</pubdate>
</paper>

<paper id="256">
<key>welbourne-cascadia</key>
<inproceedings>
<author>
<person>Evan Welbourne</person>
<person>Nodira Khoussainova</person>
<person>Julie Letchner</person>
<person>Yang Li</person>
<person>Magdalena Balazinska</person>
<person>Gaetano Borriello</person>
<person>Dan Suciu</person>
</author>
<title>Cascadia: a system for specifying, detecting, and managing RFID events</title>
<booktitle>Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MobiSys)</booktitle>
<month>--06--</month>
<year>2008</year>
<pages>281-294</pages>
<address>Breckenridge, CO, USA</address>
<doi>10.1145/1378600.1378631</doi>
<url>http://doi.acm.org/10.1145/1378600.1378631</url>
<publisher>ACM</publisher>
<abstract>Cascadia is a system that provides RFID-based pervasive computing applications 
with an infrastructure for specifying, extracting and managing meaningful 
high-level events from raw RFID data. Cascadia provides three important 
services. First, it allows application developers and even users to specify 
events using either a declarative query language or an intuitive visual 
language based on direct manipulation. Second, it provides an API that 
facilitates the development of applications which rely on RFID-based events. 
Third, it automatically detects the specified events, forwards them to 
registered applications and stores them for later use (e.g., for historical 
queries). \par We present the design and implementation of Cascadia along with 
an evaluation that includes both a user study and measurements on traces 
collected in a building-wide RFID deployment. To demonstrate how Cascadia 
facilitates application development, we built a simple digital diary 
application in the form of a calendar that populates itself with RFID-based 
events. Cascadia copes with ambiguous RFID data and limitations in an RFID 
deployment by transforming RFID readings into probabilistic events. We show 
that this approach outperforms deterministic event detection techniques while 
avoiding the need to specify and train sophisticated models. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
</inproceedings>
<pubdate>20080601</pubdate>
</paper>

<paper id="257">
<key>wietrzyk-manets_cattle</key>
<inproceedings>
<author>
<person>Bartosz Wietrzyk</person>
<person>Milena Radenkovic</person>
<person>Ivaylo Kostadinov</person>
</author>
<title>Practical MANETs for Pervasive Cattle Monitoring</title>
<booktitle>Proceedings of The Seventh International Conference on Networking (ICN 2008)</booktitle>
<address>Cancun, Mexico</address>
<volume>0</volume>
<month>--04--</month>
<year>2008</year>
<isbn>978-0-7695-3106-9</isbn>
<pages>14-23</pages>
<doi>http://doi.ieeecomputersociety.org/10.1109/ICN.2008.78</doi>
<publisher>IEEE Computer Society</publisher>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>nottingham_cattle</keywords>
<keywords>crawdad</keywords>
<refnames><refname>nottingham/cattle</refname>
</refnames>
</inproceedings>
<pubdate>20080401</pubdate>
</paper>

<paper id="258">
<key>woyach-sensorless</key>
<inproceedings>
<author>
<person>Kristen Woyach</person>
<person>Daniele Puccinelli</person>
<person>Martin Haenggi</person>
</author>
<title>Sensorless Sensing in Wireless Networks: Implementation and Measurements</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Second Workshop on Wireless Network Measurements (WiNMee 2006)</booktitle>
<address>Boston, MA, USA</address>
<month>--04--</month>
<year>2006</year>
<url>http://www.winmee.org/papers/01-02.pdf</url>
</inproceedings>
<pubdate>20060401</pubdate>
</paper>

<paper id="259">
<key>wu-experimental</key>
<inproceedings>
<author>
<person>Zhibin Wu</person>
<person>Sachin Ganu</person>
<person>Ivan Seskar</person>
<person>Dipankar Raychaudhuri</person>
</author>
<title>Experimental Investigation of PHY Layer Rate Control and Frequency Selection in 802.11-based Ad-Hoc Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the ACM SIGCOMM 2005 Workshop on experimental approaches to wireless network design and analysis (E-WIND-05)</booktitle>
<month>--08--</month>
<year>2005</year>
<address>Philadelphia, PA</address>
<url>http://www.acm.org/sigs/sigcomm/sigcomm2005/paper-WuGan.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050801</pubdate>
</paper>

<paper id="260">
<key>wu-vehicles</key>
<inproceedings>
<author>
<person>Hao Wu</person>
<person>Mahesh Palekar</person>
<person>Richard Fujimoto</person>
<person>Randall Guensler</person>
<person>Michael Hunter</person>
<person>Jaesup Lee</person>
<person>Joonho Ko</person>
</author>
<title>An Empirical Study of Short Range Communications for Vehicles</title>
<booktitle>Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks</booktitle>
<address>Cologne, Germany</address>
<month>--09--</month>
<year>2005</year>
<url>http://portal.acm.org/citation.cfm?id=1080754.1080769</url>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>gatech_vehicular</keywords>
<keywords>crawdad</keywords>
<refnames><refname>gatech/vehicular</refname>
</refnames>
</inproceedings>
<pubdate>20050901</pubdate>
</paper>

<paper id="261">
<key>xu-mobility</key>
<inproceedings>
<author>
<person>Sanlin Xu</person>
<person>Kim Blackmore</person>
<person>Haley Jones</person>
</author>
<title>Mobility Assessment for MANETs Requiring Persistent Links</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>39-44</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://portal.acm.org/citation.cfm?id=1072430.1072437</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="262">
<key>yarvis-characterization</key>
<inproceedings>
<author>
<person>Mark Yarvis</person>
<person>Konstantina Papagiannaki</person>
<person>W. Steven Conner</person>
</author>
<title>Characterization of 802.11 Wireless Networks in the Home</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the First Workshop on Wireless Network Measurements (WiNMee 2005)</booktitle>
<month>--04--</month>
<year>2005</year>
<address>Trentino, Italy</address>
<url>http://www.winmee.org/2005/papers/WiNMee_Yarvis.pdf</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050401</pubdate>
</paper>

<paper id="263">
<key>yeo-characterizing</key>
<inproceedings>
<author>
<person>Jihwang Yeo</person>
<person>Moustafa Youssef</person>
<person>Tristan Henderson</person>
<person>Ashok Agrawala</person>
</author>
<title>An Accurate Technique for Measuring the Wireless Side of Wireless Networks</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the International Workshop on Wireless Traffic Measurements and Modeling</booktitle>
<pages>13-18</pages>
<month>--06--</month>
<year>2005</year>
<address>Seattle, WA</address>
<url>http://portal.acm.org/citation.cfm?id=1072430.1072433</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20050601</pubdate>
</paper>

<paper id="264">
<key>yeo-crawdad-ccr</key>
<article>
<author>
<person>Jihwang Yeo</person>
<person>David Kotz</person>
<person>Tristan Henderson</person>
</author>
<title>CRAWDAD: A Community Resource for Archiving Wireless Data at Dartmouth</title>
<journal>ACM SIGCOMM Computer Communication Review</journal>
<year>2006</year>
<month>--04--</month>
<volume>36</volume>
<number>2</number>
<pages>21-22</pages>
<note>Project overview</note>
<url>http://doi.acm.org/10.1145/1129582.1129588</url>
<keyword>wireless network, network measurement</keyword>
<abstract>Wireless network researchers are seriously starved for data about how real 
users, applications, and devices use real networks under real network 
conditions. CRAWDAD, a Community Resource for Archiving Wireless Data at 
Dartmouth, is a new NSF-funded project to build a wireless network data archive 
for the research community. We host wireless data, and provide tools and 
documents to make it easy to collect and use wireless network data. We hope 
that this resource will help researchers identify and evaluate real and 
interesting problems in mobile and pervasive computing. This report outlines 
the CRAWDAD project, the kick-off workshop that was held at MobiCom 2005, and 
the latest news. </abstract>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>dartmouth_campus</keywords>
<keywords>crawdad</keywords>
</article>
<pubdate>20060401</pubdate>
</paper>

<paper id="265">
<key>yeo-framework</key>
<inproceedings>
<author>
<person>Jihwang Yeo</person>
<person>Moustafa Youssef</person>
<person>Ashok Agrawala</person>
</author>
<title>A Framework for Wireless LAN Monitoring and its Applications</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<booktitle>Proceedings of the Third ACM Workshop on Wireless Security (WiSe'04)</booktitle>
<pages>70-79</pages>
<month>--10--</month>
<year>2004</year>
<address>Philadelphia, PA</address>
<url>http://portal.acm.org/citation.cfm?id=1023646.1023660</url>
<category>wireless-meas</category>
</inproceedings>
<pubdate>20041001</pubdate>
</paper>

<paper id="266">
<key>yeo-wireless</key>
<techreport>
<author>
<person>Jihwang Yeo</person>
<person>Suman Banerjee</person>
<person>Ashok Agrawala</person>
</author>
<title>Measuring Traffic on the Wireless Medium: Experience and Pitfalls</title>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<number>CS-TR 4421</number>
<month>--12--</month>
<year>2002</year>
<institution>Department of Computer Science, University of Maryland</institution>
<url>http://www.cs.umd.edu/Library/TRs/CS-TR-4421/CS-TR-4421.pdf</url>
<category>wireless-meas</category>
</techreport>
<pubdate>20021201</pubdate>
</paper>

<paper id="267">
<key>yoneki-community-detection</key>
<inproceedings>
<author>
<person>Eiko Yoneki</person>
<person>Pan Hui</person>
<person>Jon Crowcroft</person>
</author>
<title>Visualizing community detection in opportunistic networks</title>
<booktitle>CHANTS '07: Proceedings of the second workshop on Challenged networks CHANTS</booktitle>
<year>2007</year>
<pages>93-96</pages>
<address>Montreal, Quebec, Canada</address>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>mit_reality</keywords>
<keywords>cambridge_haggle</keywords>
<keywords>crawdad</keywords>
<doi>http://doi.acm.org/10.1145/1287791.1287810</doi>
<url>http://doi.acm.org/10.1145/1287791.1287810</url>
<publisher>ACM Press</publisher>
<abstract>Community is an important attribute of Pocket Switched Networks (PSNs), since 
mobile devices are carried by people who tend to belong to communities in their 
social life. We discover the heterogeneity of human interactions such as 
community formation from real world human mobility traces. We have introduced 
novel distributed community detection approaches and evaluated with those 
traces. This paper describes a series of visualizations to show characteristics 
of human mobility traces including community detection. We focus on extracting 
information related to levels of clustering, network transitivity, and strong 
community structure. The progression of the connection map along the community 
formation process is also visualized. </abstract>
</inproceedings>
<pubdate>20070001</pubdate>
</paper>

<paper id="268">
<key>zhang-bus-dtn</key>
<inproceedings>
<author>
<person>Xiaolan Zhang</person>
<person>Jim Kurose</person>
<person>Brian Neil Levine</person>
<person>Don Towsley</person>
<person>Honggang Zhang</person>
</author>
<title>Study of a Bus-Based Disruption Tolerant Network: Mobility Modeling and Impact on Routing</title>
<booktitle>Proc. ACM Annual Intl. Conf. on Mobile Computing and Networking (Mobicom)</booktitle>
<month>--09--</month>
<year>2007</year>
<address>Montreal, Canada</address>
<url>http://portal.acm.org/citation.cfm?id=1287853.1287876</url>
<category>crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>umass_diesel</keywords>
<keywords>crawdad</keywords>
<refnames><refname>umass/diesel</refname>
</refnames>
</inproceedings>
<pubdate>20070901</pubdate>
</paper>

<paper id="269">
<key>zhang-hardware-zebranet</key>
<inproceedings>
<author>
<person>Pei Zhang</person>
<person>Christopher Sadler</person>
<person>Stephen Lyon</person>
<person>Margaret Martonosi</person>
</author>
<title>Hardware Design Experiences in ZebraNet</title>
<booktitle>Proceedings of the 2nd international conference on Embedded networked sensor systems (Sensys)</booktitle>
<month>--11--</month>
<year>2004</year>
<address>Baltimore, MD</address>
<publisher>ACM</publisher>
<url>http://portal.acm.org/citation.cfm?id=1031495.1031522</url>
<keyword>Sensor Networks, Sensor Deployment, ZebraNet, GPS</keyword>
<abstract>The enormous potential for wireless sensor networks to make a positive impact 
on our society has spawned a great deal of research on the topic, and this 
research is now producing environment-ready systems. Current technology limits 
coupled with widely-varying application requirements lead to a diversity of 
hardware platforms for diÂ®erent portions of the design space. In addition, the 
unique energy and reliability constraints of a system that must function for 
months at a time without human intervention mean that demands on sensor network 
hardware are different from the demands on standard integrated circuits. This 
paper describes our experiences designing sensor nodes and low level software 
to control them. In the ZebraNet system we use GPS technology to record 
fine-grained position data in order to track long term animal migrations. The 
ZebraNet hardware is composed of a 16-bit TI microcontroller, 4 Mbits of 
off-chip flash memory, a 900 MHz radio, and a low-power GPS chip. In this 
paper, we discuss our techniques for devising efficient power supplies for 
sensor networks, methods of managing the energy consumption of the nodes, and 
methods of managing the peripheral devices including the radio, flash, and 
sensors. We conclude by evaluating the design of the ZebraNet nodes and 
discussing how it can be improved. Our lessons learned in developing this 
hardware can be useful both in designing future sensor nodes and in using them 
in real systems. </abstract>
<category>wireless-meas,crawdad</category>
<keywords>measurement</keywords>
<keywords>wireless</keywords>
<keywords>princeton_zebranet</keywords>
<keywords>crawdad</keywords>
<refnames><refname>princeton/zebranet</refname>
</refnames>
</inproceedings>
<pubdate>20041101</pubdate>
</paper>

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</metameas>

